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At least 1,297 records · Page 72

High temperatures and low soil moisture synergistically reduce switchgrass yields from marginal field sites and inhibit fermentation

‘Marginal lands’ are low productivity sites abandoned from agriculture for reasons such as low or high soil water content, challenging topography, or nutrient deficiency. To avoid competition with crop production, cellulosic bioenergy crops have been proposed for cultivation on marginal lands, however on these sites they may be more strongly affected by environmental stresses such as low soil water content. In this study we used rainout shelters to induce low soil moisture on marginal lands and determine the effect of soil water stress on switchgrass growth and the subsequent production of bioethanol. Five marginal land sites that span a latitudinal gradient in Michigan and Wisconsin were planted to switchgrass in 2013 and during the 2018–2021 growing seasons were exposed to reduced precipitation under rainout shelters in comparison to ambient precipitation. The effect of reduced precipitation was related to the environmental conditions at each site and biofuel production metrics (switchgrass biomass yields and composition and ethanol production). During the first year (2018), the rainout shelters were designed with 60% rain exclusion, which did not affect biomass yields compared to ambient conditions at any of the field sites, but decreased switchgrass fermentability at the Wisconsin Central–Hancock site. In subsequent years, the shelters were redesigned to fully exclude rainfall, which led to reduced biomass yields and inhibited fermentation for three sites. When switchgrass was grown in soils with large reductions in moisture and increases in temperature, the potential for biofuel production was significantly reduced, exposing some of the challenges associated with producing biofuels from lignocellulosic biomass grown under drought conditions.

09 BIOMASS FUELS↗

SU-E-T-106: An Institutional Review of Using Commercially Available Software to Evaluate Treatment Plan Quality for Various Treatment Sites and Beam Deliveries

Purpose: Use Sun Nuclear Quality Reports™ with PlanIQ™ to evaluate different treatment delivery techniques for various treatment sites. Methods: Fifteen random patients with different treatment sites were evaluated. These include the Head/Neck, prostate, pelvis, lung, esophagus, axilla, bladder and abdomen. Initially, these sites were planned on the Pinnacle {sup 3} V9.6 treatment planning system and utilized nine 6MV step-n-shoot IMRT fields. The RT plan, dose and structure sets were sent to Quality Reports™ where a DVH was recreated and the plans were compared to a unique Plan Algorithm for each treatment site. Each algorithm has its own plan quality metrics and objectives, which include the PTV coverage, PTV maximum dose, the prescription dose outside the target, doses to the critical structures, and the global maximum dose and its location. Each plan was scored base on meeting each objective. Plans may have been reoptimized and reevaluated with Quality Reports™ based on the initial score. PlanIQ™ was used to evaluate if any objective not met was achievable or difficult to obtain. A second plan using VMAT delivery was created for each patient and scored with Quality Reports™. Results: There were a wide range of scores for the different treatment sites with some scoring better for IMRT plans and some better for the VMAT deliveries. The variation in the scores could be attributed to the treatment site, location, and shape of the target. Most deliveries were chosen for the VMAT due to the short treatment times and quick patient throughput with acceptable plan scores. Conclusion: The tools are provided for both physician and dosimetrist to objectively evaluate the use of VMAT delivery versus the step-n-shoot IMRT delivery for various sites. PlanIQ validates if objectives can be met. For the physicist, a concise pass/fail report is created for plan evaluation.

60 APPLIED LIFE SCIENCES↗

Lattice site–dependent metal leaching in perovskites toward a honeycomb-like water oxidation catalyst

Metal leaching during water oxidation has been typically observed in conjunction with surface reconstruction on perovskite oxide catalysts, but the role of metal leaching at each geometric site has not been distinguished. Here, we manipulate the occurrence and process of surface reconstruction in two model ABO 3 perovskites, i.e., SrSc 0.5 Ir 0.5 O 3 and SrCo 0.5 Ir 0.5 O 3 , which allow us to evaluate the structure and activity evolution step by step. The occurrence and order of leaching of Sr (A-site) and Sc/Co (B-site) were controlled by tailoring the thermodynamic stability of B-site. Sr leaching from A-site mainly generates more electrochemical surface area for the reaction, and additional leaching of Sc/Co from B-site triggers the formation of a honeycomb-like IrO x H y phase with a notable increase in intrinsic activity. A thorough surface reconstruction with dual-site metal leaching induces an activity improvement by approximately two orders of magnitude, which makes the reconstructed SrCo 0.5 Ir 0.5 O 3 among the best for water oxidation in acid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

EVI-EnSitePy (Electric Vehicle Infrastructure – Energy Estimation and Site Optimization Tool in Python) [EVI-X Modeling Suite] [SWR-25-07]

EVI-EnSitePy is a comprehensive agent-based tool designed for the analysis and design of high-power charging sites, encompassing a wide array of site agents including Electric Vehicles (EVs), chargers, energy storage units (ESS), renewable energy resources (DER), and loads. This versatile tool offers diverse functionalities and a modular modeling approach, allowing detailed configuration of agents based on power ratings, port numbers, energy capacities, demand requirements, charger interfaces, and flexibility to customize the tool for project specific goals. By simulating agent interactions and employing various metrics, EVI-EnSitePy enables the assessment of site performance, exploration of energy management systems (EMS), and implementation of innovative EV charging policies. Utilizing EV charge schedules and arrival states, the tool performs thorough charging site simulations, with outputs consisting of agent and site-level power profiles and statistical metrics. Employing a tree graph structure, EVI-EnSitePy supports nested site structures and power distribution modeling. The tool's ability to generate charging schedules deterministically or via stochastic analysis further enhances its versatility. Through its features and capabilities, EVI-EnSitePy offers a powerful platform for informed decision-making in the realm of high-power charging site design and operation.

Jackson, Derek [National Renewable Energy Laborato↗

Spatial Variability of Winds and HRRR–NCEP Model Error Statistics at Three Doppler-Lidar Sites in the Wind-Energy Generation Region of the Columbia River Basin

Annually and seasonally averaged wind profiles from three Doppler lidars were gathered from sites in the Columbia River basin of east-central Oregon and Washington, a major region of wind-energy production, for the Second Wind Forecast Improvement Project (WFIP2) experiment. The profile data are used to quantify the spatial variability of wind flows in this area of complex terrain, to assess the HRRR-NCEP model's ability to capture spatial and temporal variability of wind profiles, and to evaluate model errors. Annually averaged measured wind speed differences over the 70-km extent of the lidar measurements reached 1 m s -1 within the wind-turbine rotor layer, and 2 m s -1 for 200-500 m AGL. Stronger wind speeds in the lowest 500 m occurred at sites higher in elevation, farther from the river, and farther west - closer to the Cascade Mountain barrier. Validating against the lidar data, the HRRR model underestimated strong wind speeds (>12 m s -1 ) and, consequently, their frequency of occurrence, especially at the two lowest-elevation sites, producing annual low biases in rotor-layer wind speed of 0.5 m s -1 . The RMSE between measured and modeled winds at all sites was about 3 m s -1 and did not degrade significantly with forecast lead time. The nature of the model errors was different for different seasons. Furthermore, although the three sites were located in the same basin terrain, the nature of the model errors was different at each site. Thus, if only one of the sites had been instrumented, different conclusions would have been drawn as to the major sources of model error, depending on where the measurements were made.

17 WIND ENERGY↗

Mitigating Algorithmic Bias in Cancer Site Classification Models

Purpose Integrating artificial intelligence in cancer diagnostics has improved tumor classification beyond rule-based systems. Despite these advancements, these models may still encode demographic biases. We conducted a large-scale, applied bias-probing study of a deep learning–based cancer site classifier to quantify race information encoded in document embeddings. We then evaluated how performance changes when race-correlated embedding dimensions are removed in a post-training sensitivity analysis. Methods The cancer site classifier was trained using 3.5 million electronic cancer pathology reports from six of the National Cancer Institute's SEER registries. We trained a hierarchical self-attention network to generate 400-dimensional document embeddings. These embeddings were used to train two downstream, gradient-boosted decision tree classifiers: one to classify the cancer sites and another to predict racial categories. We identified overlapping features by intersecting the top 50 feature-importance rankings from the site and race models and computed their cumulative feature importance in each model. As a post hoc sensitivity analysis, we progressively pruned these overlapping dimensions, retrained the site model, and compared overall macro-F1 and accuracy, race-stratified macro-F1, and group fairness metrics on the basis of demographic parity and equalized odds before and after pruning. Results The analysis revealed minimal feature overlap between the cancer site and race prediction models, and the cumulative importance scores indicated a negligible influence of racial information on clinical predictions. Post-training pruning of overlapping features did not compromise the models' diagnostic accuracy, with a 0.07% loss in accuracy. Conclusion Our findings demonstrate that HiSAN-generated embeddings from SEER data can be used effectively in cancer site classification without significant demographic bias influencing the outcomes. Post-training pruning therefore functions as a practical audit and sensitivity check.

Shivanna, Abhishek [ORNL] (ORCID:0009000665228593)↗

Using Sequence-Specific Chemical and Structural Properties of DNA to Predict Transcription Factor Binding Sites

An important step in understanding gene regulation is to identify the DNA binding sites recognized by each transcription factor (TF). Conventional approaches to prediction of TF binding sites involve the definition of consensus sequences or position-specific weight matrices and rely on statistical analysis of DNA sequences of known binding sites. Here, we present a method called SiteSleuth in which DNA structure prediction, computational chemistry, and machine learning are applied to develop models for TF binding sites. In this approach, binary classifiers are trained to discriminate between true and false binding sites based on the sequence-specific chemical and structural features of DNA. These features are determined via molecular dynamics calculations in which we consider each base in different local neighborhoods. For each of 54 TFs in Escherichia coli, for which at least five DNA binding sites are documented in RegulonDB, the TF binding sites and portions of the non-coding genome sequence are mapped to feature vectors and used in training. According to cross-validation analysis and a comparison of computational predictions against ChIP-chip data available for the TF Fis, SiteSleuth outperforms three conventional approaches: Match, MATRIX SEARCH, and the method of Berg and von Hippel. SiteSleuth also outperforms QPMEME, a method similar to SiteSleuth in that it involves a learning algorithm. The main advantage of SiteSleuth is a lower false positive rate.

59 BASIC BIOLOGICAL SCIENCES↗

Unraveling the mechanism of recognition of the 3’ splice site of the adenovirus major late promoter intron by the alternative splicing factor PUF60

Pre-mRNA splicing is critical for achieving required amounts of a transcript at a given time and for regulating production of encoded protein. A given pre-mRNA may be spliced in many ways, or not at all, giving rise to multiple gene products. Numerous splicing factors are recruited to pre-mRNA splice sites to ensure proper splicing. One such factor, the 60 kDa poly(U)-binding splicing factor (PUF60), is recruited to sites that are not always spliced, but rather function as alternative splice sites. In this study, we characterized the interaction of PUF60 with a splice site from the adenovirus major late promoter (the AdML 3' splice site, AdML3’). We found that the PUF60–AdML3’ dissociation constants are in the micromolar range, with the binding affinity predominantly provided by PUF60’s two central RNA recognition motifs (RRMs). A 1.95 Å crystal structure of the two PUF60 RRMs in complex with AdML3’ revealed a dimeric organization placing two stretches of nucleic acid tracts in opposing directionalities, which can cause looping of nucleic acid and explain how PUF60 affects pre-mRNA geometry to effect splicing. Solution characterization of this complex by light-scattering and UV/Vis spectroscopy suggested a potential 2:1 (PUF60 2 :AdML3’) stoichiometry, consistent with the crystal structure. This work defines the sequence specificity of the alternative splicing factor PUF60 at the pre-mRNA 3’ splice site. Our observations suggest that control of pre-mRNA directionality is important in the early stage of spliceosome assembly, and advance our understanding of the molecular mechanism by which alternative and constitutive splicing factors differentiate among 3’ splice sites.

59 BASIC BIOLOGICAL SCIENCES↗

Subsurface electrical conductivity across the BEO site inferred using a capacitively coupled resistivity survey in May 2013, Utqiagvik, Alaska

Multiple transects across and around the Barrow Environmental Observatory (BEO) site were surveyed using a capacitively coupled resistivity tool to infer the subsurface electrical conductivity in the top ~6 m in order to improve the understanding of heterogeneity in ice and salinity content. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The acquisition was performed in May 2013 using a capacitively coupled resistivity tool (OhmMapper from Geometrics, Inc) mounted behind a sled hooked to a snowmobile. Twenty-eight ~750 m long transects cover the NGEE intensive site (polygon areas A, B, C, D) in the BEO with a measurement (apparent resistivity for 5 different geometries) taken every 1.5 to 2 m. The survey also includes other transects that have been acquired along Electrical Resistivity Tomography (ERT) transects previously acquired at the site (Site 0, AB, and BD), and several long transects (up to 7 km each) around the BEO site crossing several Drained Thawed Lake Basins (DTLB). The various transects acquired during this survey cover a distance of about 100 km. All the datasets are provided with the acquisition geometry and the associated subsurface apparent electrical conductivity. In addition, the 28 transects at the BEO intensive site were inverted to infer the subsurface electrical conductivity. Unprocessed and processed data products are included in this package. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska, and 2) multiple areas in the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

COMPASS-FME Synoptic Sites Level 1 Sensor Data v1-2

This is the version 1-2 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems.L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds and out-of-service flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project**This dataset includes:- An overall dataset README file that describes the current version, gives citation and contact information, etc.- Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year.- Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site.- Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v1-2 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning.

54 ENVIRONMENTAL SCIENCES↗

COMPASS-FME Synoptic Sites Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-0 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux CA-NS1 UCI-1850 burn site

This is the AmeriFlux version of the carbon flux data for the site CA-NS1 UCI-1850 burn site. Site Description - The UCI-1850 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗

AmeriFlux CA-NS2 UCI-1930 burn site

This is the AmeriFlux version of the carbon flux data for the site CA-NS2 UCI-1930 burn site. Site Description - The UCI-1930 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗

AmeriFlux CA-NS3 UCI-1964 burn site

This is the AmeriFlux version of the carbon flux data for the site CA-NS3 UCI-1964 burn site. Site Description - The UCI-1964 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗

AmeriFlux CA-NS4 UCI-1964 burn site wet

This is the AmeriFlux version of the carbon flux data for the site CA-NS4 UCI-1964 burn site wet. Site Description - The UCI-1964 wet site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗

AmeriFlux CA-NS5 UCI-1981 burn site

This is the AmeriFlux version of the carbon flux data for the site CA-NS5 UCI-1981 burn site. Site Description - The UCI-1981 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗

AmeriFlux CA-NS6 UCI-1989 burn site

This is the AmeriFlux version of the carbon flux data for the site CA-NS6 UCI-1989 burn site. Site Description - The UCI-1989 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗

AmeriFlux CA-NS7 UCI-1998 burn site

This is the AmeriFlux version of the carbon flux data for the site CA-NS7 UCI-1998 burn site. Site Description - The UCI-1998 site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗