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At least 109 records · Page 6

Data for "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding"

This dataset contains data used for the paper "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding". The Related References field will be updated with a full citation when available.Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_3Soils_2021 (DOI: 10.5281/zenodo.4792655).

54 ENVIRONMENTAL SCIENCES↗

Clustering of graphs with of multiple edge types.

We study clustering on graphs with multiple edge types. Our main motivation is that similarities between objects can be measured in many different metrics. For instance similarity between two papers can be based on common authors, where they are published, keyword similarity, citations, etc. As such, graphs with multiple edges is a more accurate model to describe similarities between objects. Each edge/metric provides only partial information about the data; recovering full information requires aggregation of all the similarity metrics. Clustering becomes much more challenging in this context, since in addition to the difficulties of the traditional clustering problem, we have to deal with a space of clusterings. We generalize the concept of clustering in single-edge graphs to multi-edged graphs and investigate problems such as: Can we find a clustering that remains good, even if we change the relative weights of metrics? How can we describe the space of clusterings efficiently? Can we find unexpected clusterings (a good clustering that is distant from all given clusterings)? If given the groundtruth clustering, can we recover how the weights for edge types were aggregated?

99 GENERAL AND MISCELLANEOUS↗

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

The impact of freeze-thaw history on soil carbon response to experimental freeze-thaw cycles

This dataset contains data used for the paper "The impact of freeze-thaw history on soil carbon response to experimental freeze-thaw cycles". The Related References field will be updated with a full citation when available.Freeze-thaw is a disturbance process in cold regions where permafrost soils are becoming vulnerable to temperature fluctuations above 0˚C. Freeze-thaw alters soil physical and biogeochemical properties with implications for carbon persistence and emissions in Arctic landscapes. We examined whether different freeze-thaw histories in two soil systems led to contrasting biogeochemical responses under a laboratory-controlled freeze-thaw incubation. We investigated controls on soil organic matter (SOM) composition through Fourier-transform ion cyclotron resonance mass spectroscopy (FT-ICR-MS) to identify nominal carbon oxidation states and relative abundances of aliphatic-type carbon molecules in both surface and subsurface soils. Soil cores (~ 60 cm-depth) were sampled from two sites in Alaskan permafrost landscapes with different in situ freeze-thaw characteristics: Healy (>40 freeze-thaw cycles annually) and Toolik (<150 freeze-thaw cycles annually). FT-ICR-MS was coupled with in situ temperature data and soil properties (i.e., soil texture, mineralogy) to assess (1) differences in SOM composition associated with previous freeze-thaw history and (2) sensitivity to experimental freeze-thaw in the extracted cores. Control (freeze-only) samples showed greater carbon oxidation in Healy soils compared with Toolik, even in lower mineral horizons where freeze-thaw history was comparable across both sites. Healy showed the most loss of carbon compounds following experimental freeze-thaw in the lower mineral depths, including a decrease in aliphatics. Toolik soils responded more slowly to freeze-thaw as shown by intermediary carbon oxidation distributed across multiple carbon compound classes. Variations in the response of permafrost carbon chemistry to freeze-thaw is an important factor for predicting changes in soil function as permafrost thaws in high northern latitudes.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/Erin-Rooney/FTC-FTICR (DOI 10.5281/zenodo.6533064).

54 ENVIRONMENTAL SCIENCES↗

Monoterpene emission data during 2015/2016 El Nino in Manaus, Brazil

This dataset contains leaf and ecosystem monoterpene emissions and normalized ratios as a function of leaf and canopy temperature during the 2015/6 El Nino in the central Amazon. Also included are 13 C-labeled monoterpene data during leaf photosynthesis under 13 CO 2 . Data was used in the publication, "Monoterpene ‘thermometer’of tropical forest-atmosphere response to climate warming." See the below Dataset Reference field for the complete publication citation.

54 ENVIRONMENTAL SCIENCES↗

Mosaicked Historic Airborne Imagery from Seward Peninsula, Alaska, Starting in the 1950's

Historical airborne imagery for each Seward Peninsula NGEE Arctic site - Teller, Kougarok, Council - were obtained with multiple years for each site in order to identify landscape changes over time when compared to more recent imagery. This dataset includes mosaicked, geolocated and, where possible, orthorectified, historic airborne and recent satellite imagery. The older photos were sourced from the USGS Earth Explorer site and the newer, satellite imagery is from the Statewide Digital Mapping Initiative (SDMI) project managed by the Geographic Information Network of Alaska on behalf of the state of Alaska. Check with Jessica Cherry (jessica.cherry@alaska.edu), University of Alaska, and Lisa Wirth (lisa@gina.alaska.edu), Geographic Information Network of Alaska (GINA) and the Statewide Digital Mapping Initiative (SDMI), for citation information and redistribution restrictions of the imagery. Dataset includes the following types of files: *.tif, *.txt, *.pdf, *.jpg, *.xml. Please refer to metadata files included inside the data folders for detailed descriptions of the data products. The use of historical aerial photographs in combination with more recent satellite imagery has proven effective at detecting and quantifying landscape changes. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort 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 on 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↗

Social Media Analytics Relevant to TikTok - a Literature Review and Directions for Future Research

We have attempted to capture a sense of the scientific state of the art in studying social media platforms, including data collection from platforms, understanding platform behavior, known adversarial uses, and adverse content detection, classification, and quantification. Our coverage of the field is backed up by roughly two hundred citations, and it concludes with a comparative analysis and a list of apparent gaps and potential paths forward.

99 GENERAL AND MISCELLANEOUS↗

The vapor pressures of explosives

The vapor pressures of many explosive compounds are extremely low and thus determining accurate values proves difficult. Many researchers, using a variety of methods, have measured and reported the vapor pressures of explosives compounds at single temperatures, or as a function of temperature using vapor pressure equations. There are large variations in reported vapor pressures for many of these compounds, and some errors exist within individual papers. This article provides a review of explosive vapor pressures and describes the methods used to determine them. We have compiled primary vapor pressure relationships traceable to the original citations and include the temperature ranges for which they have been determined. Corrected values are reported as needed and described in the text. In addition, after critically examining the available data, we calculate and tabulate vapor pressures at 25 °C.

explosive, vapor pressure, NG, TNT, PETN, RDX↗

Conceptual design study of small long-life PWR based on thorium cycle fuel

A neutronic performance of small long-life Pressurized Water Reactor (PWR) using thorium cycle based fuel has been investigated. Thorium cycle which has higher conversion ratio in thermal region compared to uranium cycle produce some significant of {sup 233}U during burn up time. The cell-burn up calculations were performed by PIJ SRAC code using nuclear data library based on JENDL 3.3, while the multi-energy-group diffusion calculations were optimized in whole core cylindrical two-dimension R-Z geometry by SRAC-CITATION. this study would be introduced thorium nitride fuel system which ZIRLO is the cladding material. The optimization of 350 MWt small long life PWR result small excess reactivity and reduced power peaking during its operation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CT_Data_of_Gas_Migration_in_Setting_Cement

Computed tomography experimental data associated with the submitted manuscript "Migration of air bubbles in a column of cement slurry" by N’dri Arthur Konan, Eilis Rosenbaum, Dustin Crandall, Mehrdad Massoudi. Full description with citation to be updated when manuscript is accepted.

Computed Tomography↗

Wind Turbine Oil and Gas Pipeline Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from oil and gas pipelines. A setback requirement is a minimum distance from a pipeline that an energy project may be developed. As of April 2022, no ordinances were discovered for any counties. Such ordinances are likely to arise as regulations continue to expand. Therefore, this dataset applies a median setback equivalent to 1.1 times the turbine tip-height, sourced from trends in other infrastructure. A TIF data file and a PNG map of the data are provided, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

Topography and canopy cover influence soil organic carbon composition and distribution across a forested hillslope in the discontinuous permafrost zone

This dataset contains data used for the paper "Topography and canopy cover influence soil organic carbon composition and distribution across a forested hillslope in the discontinuous permafrost zone". The Related References field will be updated with a full citation when available. Topography and canopy cover influence ground temperature in warming permafrost landscapes, yet soil temperature heterogeneity introduced by meso-topographic slope positions, microtopographic differences in vegetation cover, and the subsequent impact of contrasting temperature conditions to soil organic carbon (SOC) dynamics are understudied. Buffering of permafrost-affected soils against warming air temperatures in boreal forests can reflect surface soil characteristics (e.g., thickness of organic material) as well as the degree and type of canopy cover (e.g., open cover vs closed cover). Both landscape and soil properties interact to determine meso- and micro-scale heterogeneity of ground warming. We sampled a hillslope catena transect in a discontinuous permafrost zone near Fairbanks, Alaska to test the small-scale (1 to 3 meter) impacts of slope position and cover type on soil organic matter composition. Mineral active layer samples were collected from backslope, low backslope, and footslope positions at depths spanning 19 to 60 cm. We examined soil mineralogical composition, soil moisture, total carbon and nitrogen content, and organic mat thickness in conjunction with an assessment of SOC composition using Fourier-transform ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS). Soils in the footslope position had a higher relative contribution of lignin-like compounds while backslope soils had more aliphatic and condensed aromatic compounds as determined by FT-ICR-MS. The effect of open versus closed tree canopy cover varied with slope position. On the backslope, we found higher oxidation of molecules under open cover compared with closed cover, indicating an effect of warmer soil temperature on decomposition. Little to no effect of canopy was observed for soils at the footslope position, which we attributed, in part, to the strong impact of soil moisture content in SOC dynamics in the water-gathering footslope position. The thin organic mat under open cover on the backslope position may have contributed to differences in soil temperature and thus SOC oxidation under open and closed canopy. Here, the thinner organic mat did not appear to buffer the underlying soil against warm season air temperatures and thus increased SOC decomposition as indicated by higher oxidation of SOC molecules and a lower contribution of simple molecules under open cover compared with the closed canopy sites. Our findings suggest that the role of canopy cover in SOC dynamics varies as a function of landscape position and soil properties, namely organic mat thickness and soil moisture. Condition-specific heterogeneity of SOC composition under open and closed canopy cover highlights the protective effect of canopy cover for soils on backslope positions. This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/Erin-Rooney/Y1_fairbanks (DOI: 10.5281/zenodo.8071247).

54 ENVIRONMENTAL SCIENCES↗

Hot Droughts and Forest Tree Dynamics in the Amazon - Statistical Models, Scripts, Data, and Outputs

This package contains data, outputs, equations, and R scripts for analyses for manuscript entitled "Hot droughts in the Amazon: A window to a future hypertropical climate" by J. Chambers et al., in particular it contains statistical models and analyses for the INPA BIONTE tree mortality study. The Models folder contains details for all statistical models in PDF files. The Scripts folder contains the R scripts for Bayesian Hierarchical Models (two text files) and SEMs (one text file) are separate and reasonably annotated. All data associated with these scripts are in the data folder. The Data folder contains two of the three CSV files used for the analyses and are called by the R scripts. Two of them are part of published datasets (`BIONTE_mortality-rates.csv` from Lima et al. 2024, DOI:10.15486/ngt/1898910 and `SPEI.csv` from Pastorello et al. 2023 DOI:10.15486/ngt/1958257) and also provided in this package for convenience (please see the corresponding datasets for usage and citation terms). The third dataset (`BIONTE_gapfilled_wd.csv`) contains sensitive information and can be obtained by contacting the manuscript lead author. The Outputs folder contains the two output files that provide extra information about the analyses. The file `figuresFeb2025d.pdf` contains all the figures from the manuscript - captions are in the manuscript. The file `ChambersMS.pdf` contains primary results from Bayesian statistical models, regression analyses, and validation steps applied to the tree mortality data from the INPA experiments. The document includes visual summaries, model diagnostics, and leave-one-out (LOO) validation results. A breakdown of file contents can be found in the README file that is part of this package.

54 ENVIRONMENTAL SCIENCES↗

Semantic Property Graph for Scalable Knowledge Graph Analytics

Graphs are a natural and fundamental representation to describe entities, relationships, activities, and evolution of complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Resource Description Framework (RDF) and Labeled Property Graph (LPG) are two of the most used data models to encode information in a graph. Both models are similar in terms of using basic graph elements such as nodes and edges but differ in terms of the modeling approach, expressibility, serialization, and target applications. RDF is a flexible data exchange model for expressing information about entities but it tends to a have high memory footprint and inefficient storage, which does not make it a natural choice to perform scalable graph analytics. In contrast, LPG has gained traction as a reliable model to perform scalable graph analytic tasks such as sub-graph matching, network alignment, and real-time knowledge graph query. It provides efficient storage, fast traversal, and flexibility to model various real-world domains. At the same time, the LPG lacks the support of a formal knowledge representation such as an ontology to provide automated knowledge inference. We propose Semantic Property Graph (SPG) as a logical projection of reified RDF into the LPG model. SPG continues to use RDF ontology to define the type hierarchy of the projected graph and validate it against a given ontology. We present a framework to convert reified RDF graphs into SPG using two different computing environments. We also present cloud-based graph migration capabilities using Amazon Web Services.

Purohit, Sumit↗

U.S. Wind Siting Regulation and Zoning Ordinances

A collection of documented wind siting ordinances at the state, county, township, and local level throughout the United States. The data were compiled from several sources including, DOE's Wind Exchange Ordinance Database (https://windexchange.energy.gov/policies-incentives), National Conference of State and Legislatures Wind Energy Siting (https://www.ncsl.org/research/energy/state-wind-energy-siting.aspx), and scholarly legal articles. The citations for each ordinance are included in the spreadsheet.

A-weighted decibel↗

Wind Turbine Water Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from water based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from water that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 1.1 times the turbine tip-height was applied in counties that lacked specific water setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

Wind Turbine Transmission Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from transmission based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from transmission infrastructure that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 1.1 times the turbine tip-height was applied in counties that lacked specific transmission setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗

Wind Turbine Structure Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from structures based on existing county ordinances as of April 2022. A setback requirement is a minimum distance from a structure that an energy project may be developed, and these varied widely across the counties in which they existed. Two versions are provided: one reflecting only the county ordinances and another incorporating extrapolated trends. In the extrapolated version, a median setback equivalent to 2 times the turbine tip-height was applied in counties that lacked specific structure setback regulations. A TIF data file and a PNG map of the data are provided for both versions, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗