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DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

DNDCe↗

DOE OSTI2019

SoyCSN: Soybean context-specific network analysis and prediction based on tissue-specific transcriptome data

The Soybean Gene Atlas project provides a comprehensive map for understanding gene expression patterns in major soybean tissues from flower, root, leaf, nodule, seed, and shoot and stem. The RNA-Seq data generated in the project serve as a valuable resource for discovering tissue-specific transcriptome behavior of soybean genes in different tissues. We developed a computational pipeline for Soybean context-specific network (SoyCSN) inference with a suite of prediction tools to analyze, annotate, retrieve, and visualize soybean context-specific networks at both transcriptome and interactome levels. BicMix and Cross-Conditions Cluster Detection algorithms were applied to detect modules based on co-expression relationships across all the tissues. Soybean context-specific interactomes were predicted by combining soybean tissue gene expression and protein–protein interaction data. Functional analyses of these predicted networks provide insights into soybean tissue specificities. For example, under symbiotic, nitrogen-fixing conditions, the constructed soybean leaf network highlights the connection between the photosynthesis function and rhizobium–legume symbiosis. SoyCSN data and all its results are publicly available via an interactive web service within the Soybean Knowledge Base (SoyKB) at http://soykb.org/SoyCSN. SoyCSN provides a useful web-based access for exploring context specificities systematically in gene regulatory mechanisms and gene relationships for soybean researchers and molecular breeders.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

DRoP: Automated detection of conserved solvent‐binding sites on proteins

Abstract Water and ligand binding play critical roles in the structure and function of proteins, yet their binding sites and significance are difficult to predict a priori. Multiple solvent crystal structures (MSCS) is a method where several X‐ray crystal structures are solved, each in a unique solvent environment, with organic molecules that serve as probes of the protein surface for sites evolved to bind ligands, while the first hydration shell is essentially maintained. When superimposed, these structures contain a vast amount of information regarding hot spots of protein‐protein or protein‐ligand interactions, as well as conserved water‐binding sites retained with the change in solvent properties. Optimized mining of this information requires reliable structural data and a consistent, objective analysis tool. Detection of related solvent positions (DRoP) was developed to automatically organize and rank the water or small organic molecule binding sites within a given set of structures. It is a flexible tool that can also be used in conserved water analysis given multiple structures of any protein independent of the MSCS method. The DRoP output is an HTML format list of the solvent sites ordered by conservation rank in its population within the set of structures, along with renumbered and recolored PDB files for visualization and facile analysis. Here, we present a previously unpublished set of MSCS structures of bovine pancreatic ribonuclease A (RNase A) and use it together with published structures to illustrate the capabilities of DRoP.

Kearney, Bradley M.↗

DOE OSTI2022

Nonlinear spectral analysis of ion acoustic solitons arising from a streaming charged object using the numerical inverse scattering transform

Observations of nonlinear coherent plasma phenomena in spacecraft and terrestrial experiments often rely on visual identification of solitary modes because nonlinear coherent modes are broadband in a Fourier transform based analysis. We implement an alternative spectral decomposition known as the inverse scattering transform and demonstrate its ability to successfully isolate nonlinear modes on the homogeneous and forced Korteweg–De Vries equation which models these nonlinear modes. We also demonstrate for the first time that this decomposition is useful when forcing is applied. This is because the stable modes generated by localized forcing are similar to the homogeneous solutions where the inverse scattering transform is a rigorous decomposition. This spectral technique is then applied to simulations of ion acoustic waves generated by a 10 mm spherical debris object interacting with the ionospheric plasma orbiting at 2000 km altitude. The algorithm is found to successfully detect the resultant solitons. This demonstrates the feasibility of using this spectral technique as a real time analysis tool for screening spacecraft data for nonlinear solitary modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants

Abstract FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Connecting AmeriFlux to the Globe, Extending the Partnership with Global Flux Network FLUXNET

We propose a project that will extend and expand the activities and contributions of AmeriFlux, to the global stage by working with our international partners to continue operating and expand the functioning of global FLUXNET database. One goal is to produce the next-generation FLUXNET dataset. This will be an integrated dataset on carbon, water and energy fluxes, on meteorological conditions and on the structure and function of the ecosystems; we have to potential to construct a new database, double the size of the La Thuile dataset, with over 2000 site-years of trace gas flux measurements, and supporting meteorological and site meta-data from over 400 sites world-wide. The production of the next FLUXNET database is critical to the activities of this ROSE’s solicitation because these data will drive many of the carbon cycle synthesis activities and the model parameterization and validation activities. A second goal is to build the next-generation, data-system that will house, distribute and query data and discover new information by the broader biogeoscience user community. The third goal is to use these data in synthesis activities that improve our understanding on how climate, weather, ecological, physiological and soil factors govern the exchange of carbon, water and energy between vegetation and the atmosphere at multiple time and space scales. The fourth goal is to act as a coordinator of the project to recruit data, to organize a workshop/conference and to build a community of data sharing and interaction across vast cultural spectrum of participating scientists. The rationale for proposing this work is based on the fact that the vast databases that are produced by flux networks cannot perpetuate and evolve without continued support of the intellectual activities of scientists who produce data, expert in databases, and scientists who use data for modeling. The actuality of a flux network takes human intervention to recruit data from different countries and cultures, to build trust to share data in open-access format, to support data users, and to collaborate. Specifically, we will develop an updated data portal that is easy to navigate and conducive for distributing, visualization, evaluation and discovery of the multiple types of flux and environmental data and information. We will foster collaboration and interactions with our national and international partners and the recruitment of data by: 1) continuing the periodic publication of the newsletter, FLUXLETTER; 2) by hosting an international conference; 3) by coordinating and launching multi-investigator data synthesis activities; and 4) by developing tools that coordinate the development of research papers resulting from the dataset. Data products include raw and gap-filled data at their native time steps (30 minute averages), data products that are integrated on daily and annual time scales and value added products like ecosystem respiration and canopy photosynthesis. Uncertainty analysis and quality control metrics will be produced in coordination with AmeriFlux and ICOS. We will also work with colleagues to expand the scope of FLUXNET beyond carbon dioxide and water vapor, and start archiving the growing methane flux databases that are being collected, world-wide. The interpretation of the flux data relies on good meta-data. We will work with data providers to populate and expand the meta-data archives. We will also work with collaborators to incorporate data from remote sensing products such as MODIS and Landsat, from corresponding climate and weather stations. Another goal is to incorporate new data on canopy structure, with recent LIDAR acquisitions, to populate the data archive with automated soil respiration and understory flux measurements, where available and local climate records for corresponding sites. And, we will collaborate with the TRY database, by merging flux data with plant trait information.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

An LCO-responsive homolog of NODULE INCEPTION positively regulates lateral root formation in Populus sp.

Abstract The transcription factor NODULE INCEPTION (NIN) has been studied extensively for its multiple roles in root nodule symbiosis within plants of the nitrogen-fixing clade (NFC) that associate with soil bacteria, such as rhizobia and Frankia. However, NIN homologs are present in plants outside the NFC, suggesting a role in other developmental processes. Here, we show that the biofuel crop Populus sp., which is not part of the NFC, contains eight copies of NIN with diversified protein sequence and expression patterns. Lipo-chitooligosaccharides (LCOs) are produced by rhizobia and a wide range of fungi, including mycorrhizal ones, and act as symbiotic signals that promote lateral root formation. RNAseq analysis of Populus sp. treated with purified LCO showed induction of the PtNIN2 subfamily. Moreover, the expression of PtNIN2b correlated with the formation of lateral roots and was suppressed by cytokinin treatment. Constitutive expression of PtNIN2b overcame the inhibition of lateral root development by cytokinin under high nitrate conditions. Lateral root induction in response to LCOs likely represents an ancestral function of NIN retained and repurposed in nodulating plants, as we demonstrate that the role of NIN in LCO-induced root branching is conserved in both Populus sp. and legumes. We further established a visual marker of LCO perception in Populus sp. roots, the putative sulfotransferase PtSS1 that can be used to study symbiotic interactions with the bacterial and fungal symbionts of Populus sp.

Irving, Thomas B. (ORCID:0000000330404543)↗

DOE OSTI2023

Nuclear Trade Atlas 2016-2020

Building on prior work developing a Strategic Trade Atlas promoting understanding of global trade flows of strategic goods, a Nuclear Trade Atlas was developed based on publicly available trade data. The Nuclear Trade Atlas examines trade patterns and trends for seventeen commodities based on a two-step assessment of the trade’s nuclear relevance: first estimating the probability that trade classified under a given Harmonized System (HS) code represents a specific commodity included in the export control lists of the Nuclear Suppliers Group, and second estimating the probability that the listed, often dual-use, commodity would be indicative of nuclear use. These estimates combine to provide a measure of the likelihood trade classified under a given HS code may be nuclear relevant. By exclusively focusing on the HS codes most highly ranked by this measure, the resulting data visualizations comprising the Nuclear Trade Atlas provide those responsible for regulating or monitoring nuclear trade greater understanding of relevant global trading patterns and trends. The Atlas includes both commodity- and country-based views of nuclear trade. It is published as a book and as an interactive tool. Besides trade data, the interactive Atlas also includes data about countries’ non-proliferation commitments, allowing users to take this information into consideration while analyzing specific trade flows.

strategic trade, world customs organization, trade↗

DOE OSTI2019

Visualizing percolation and ion transport in hybrid solid electrolytes for Li–metal batteries

Hybrid solid electrolytes are composed of organic (polymer) and inorganic (ceramic) ion conducting materials, and are promising options for large-scale production of solid state lithium–metal batteries. Hybrid solid electrolytes containing 15 vol% Al-LLZO demonstrate optimal ionic conductivity properties. Ionic conductivity is shown to decrease at high inorganic loadings. This optimum is most obvious above the melting temperature of polyethylene oxide where the polymer is amorphous. Structural analysis using synchrotron nanotomography reveals that the inorganic particles are highly aggregated. The aggregation size grows with inorganic content and the largest percolating clusters measured for 5 vol%, 15 vol% and 50 vol% were ~12 μm 3 , 206 μm 3 , and 324 μm 3 , respectively. Enhanced transport in hybrid electrolytes is shown to be due to polymer|particle (Al-LLZO) interactions and ionic conductivity is directly related to the accessible surface area of the inorganic particles within the electrolyte. Finally, ordered and well-dispersed structures are ideal for next generation hybrid solid electrolytes.

25 ENERGY STORAGE↗

DOE OSTI2020

Production Operations Management System (POMS) for Fermilab Experiments

The Production Operations Management System (POMS) software allows production teams and analysis groups across multiple Fermilab experiments to launch, modify and monitor large scale campaigns of related Monte Carlo or data processing jobs, and currently manages the majority of production computing of experiments at Fermilab.POMS provides a web service interface that enables automated job submission on distributed resources according to customers’ requests, as well as subsequent monitoring of those submissions as well as recovery of failed submissions, debugging and record keeping.POMS interfaces with existing HEP data access, processing, movement and monitoring tools at Fermilab, including Jobsub (for job submission), SAM (for data management), and Landscape (for monitoring), and in combination with them handles the creation of intermediate datasets of files for multistage campaigns.POMS visualizes these campaigns with an interactive GUI interface. An important feature of POMS is a one-to-one connection between the GUI campaign visualizer and a text based representation of the complete campaign configuration. An extensible library of template campaign configurations is available. The templates are user modifiable and map cleanly to and from the GUI description of the campaign.This paper will discuss the current usage, history, and some technical details of POMS, as well as planned future extensions, particularly interfacing with Rucio as well as SAM for file movement.

Mengel, Marc↗

DOE OSTI2023

The Effect of Laser Cutting Heuristic Presentation Modality on Design Learning

Abstract The goal of this work is to study the way student designers use heuristics to effectively design for laser-cut manufacturing methods. With the recent advent of academic makerspaces, digital fabrication tools like laser cutters are relatively new additions to the classroom. Therefore, there is a gap in formal education or training on these tools, and students can find it challenging to design effectively for them. A study was performed to investigate the way students apply heuristics to redesign laser-cut assemblies when received in different modalities. All participants were given an identical lecture on laser cutting heuristics. Then, a redesign problem was presented to students, and three different experimental groups were given the heuristics in different modalities: Text-Only, text with Visual aids, and text with Tactile aids. The novelty and quality of each of the resulting redesigns were evaluated. It was hypothesized that participants would have more difficulty interpreting and applying the Text-Only heuristics, lowering the quality of their redesigned solutions relative to the other two conditions. It was also hypothesized that participants would experience fixation caused by interacting with the tactile aids, leading to the lower novelty of their redesigned solutions relative to the other two conditions. Results showed that modality played a significant role in participants’ feelings of self-efficacy after the intervention, as well as in their understanding of laser cutter design skills when responding to quiz-style questions. However, analysis of novelty and quality showed little significant impact of the intervention and varying modalities on participants’ designs.

Engineering↗

DOE OSTI2020

Phase-contrast 3D tomography of HeLa cells grown in PLLA polymer electrospun scaffolds using synchrotron X-rays

Advanced imaging is useful for understanding the three-dimensional (3D) growth of cells. X-ray tomography serves as a powerful noninvasive, nondestructive technique that can fulfill these purposes by providing information about cell growth within 3D platforms. There are a limited number of studies taking advantage of synchrotron X-rays, which provides a large field of view and suitable resolution to image cells within specific biomaterials. In this study, X-ray synchrotron radiation microtomography at Diamond Light Source and advanced image processing were used to investigate cellular infiltration of HeLa cells within poly L-lactide (PLLA) scaffolds. This study demonstrates that synchrotron X-rays using phase contrast is a useful method to understand the 3D growth of cells in PLLA electrospun scaffolds. Two different fiber diameter (2 and 4 µm) scaffolds with different pore sizes, grown over 2, 5 and 8 days in vitro , were examined for infiltration and cell connectivity. After performing visualization by segmentation of the cells from the fibers, the results clearly show deeper cell growth and higher cellular interconnectivity in the 4 µm fiber diameter scaffold. Finally, this indicates the potential for using such 3D technology to study cell–scaffold interactions for future medical use.

3D culture↗

DOE OSTI2023

Driving Next-Generation Workflows from the Data Plane

We observe the emergence of a new generation of scientific workflows that process data produced at a sustained rate by scientific instruments and large scale numerical simulations. This data is consumed by multiple analysis, visualization, or Machine Learning components not only to enable inference and justify the scientific program, but also to monitor and steer the evolution of these experiments. In such workflows, moving intermediate data efficiently is key to performance, more than efficiently scheduling computational tasks. However, most traditional workflow management systems focus on optimizing task scheduling and then deal with data management, assuming a “move little, compute for long” model, which makes them unfit to the efficient management of this new generation of workflows. Therefore, we advocate for a new way to manage scientific workflows. We propose to consider an efficiently and independently managed data plane that can store and stream data. Workflows compute components, in the application plane can then interact with the data plane, abstracted from complexities of data management. Then, the role of a workflow management system would become that of a control plane that allows users to connect services together to execute the workflow and manages connections between the application and data planes. In this position paper, we characterize several next-generation workflow motifs and describe how their interaction with the data plane is a challenge to traditional workflow management systems. Then, we express a set of requirements that a workflow management system should meet to efficiently manage next-generation workflows at different scales. Based on these requirements, we expose our vision of driving next-generation workflows from the data plane and list remaining open challenges.

Suter, Fred↗

DOE OSTI2024

Direct observation of a magnetic-field-induced Wigner crystal

Wigner predicted that when the Coulomb interactions between electrons become much stronger than their kinetic energy, electrons crystallize into a closely packed lattice. A variety of two-dimensional systems have shown evidence for Wigner crystals (WCs). However, a spontaneously formed classical or quantum WC has never been directly visualized. Neither the identification of the WC symmetry nor direct investigation of its melting has been accomplished. Here we use high-resolution scanning tunnelling microscopy measurements to directly image a magnetic-field-induced electron WC in Bernal-stacked bilayer graphene and examine its structural properties as a function of electron density, magnetic field and temperature. At high fields and the lowest temperature, we observe a triangular lattice electron WC in the lowest Landau level. The WC possesses the expected lattice constant and is robust between filling factor ν ≈ 0.13 and ν ≈ 0.38 except near fillings where it competes with fractional quantum Hall states. Increasing the density or temperature results in the melting of the WC into a liquid phase that is isotropic but has a modulated structure characterized by the Bragg wavevector of the WC. At low magnetic fields, the WC unexpectedly transitions into an anisotropic stripe phase, which has been commonly anticipated to form in higher Landau levels. Furthermore, analysis of individual lattice sites shows signatures that may be related to the quantum zero-point motion of electrons in the WC lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications

With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First, the utilization of black box models (e.g., deep neural networks) calls for advanced techniques in exploring and interpreting model behaviors. Second, the rapid growth in computing has produced enormous datasets that require techniques that can handle millions or more samples. Although some solutions to these interpretability challenges have been proposed, they typically do not scale beyond thousands of samples, nor do they provide the high-level intuition scientists are looking for. Here, we present the first scalable solution to explore and analyze high-dimensional functions often encountered in the scientific data analysis pipeline. By combining a new streaming neighborhood graph construction, the corresponding topology computation, and a novel data aggregation scheme, namely topology aware datacubes, we enable interactive exploration of both the topological and the geometric aspect of high-dimensional data. Following two use cases from high-energy-density (HED) physics and computational biology, we demonstrate how these capabilities have led to crucial new insights in both applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Dispersion curve regression – assisted wideband local wavenumber analysis for characterizing three-dimensional (3D) profile of hidden corrosion damage

Corrosion as common damage in civil, petrochemical, nuclear, and aerospace structures affects the integrity and safety of the structures and may lead to catastrophic failures. This paper presents dispersion curve regression-assisted local wavenumber analysis method, which can analyze the time–space wavefield containing wideband information of wave-damage interaction and further extract the structural information carried by such wavefield for characterizing hidden corrosion damage in an isotropic plate. To acquire the time–space wavefield, a noncontact scanning laser Doppler vibrometer is used. In our analysis method, the acquired time–space wavefield is firstly processed to generate a local wavenumber function. The derived wavenumber function is further analyzed with a dispersion curve regression step, which searches in a set of theoretical frequency-wavenumber dispersion curves for different plate thicknesses and identifies the optimal plate thickness whose theoretical curve best matches the frequency-wavenumber relation contained in the local wavenumber function. By this means, a 3D profile including both in plane and thickness dimensions of the structure can be constructed for corrosion visualization and quantification. The experimental study demonstrates that our method can quantify the profile of hidden uniform corrosion in metal plates in terms of its in-plane shape and size as well as its out-of-plane depth in the subwavelength scale. Moreover, compared to previous Lamb wave-based corrosion inspection methods, our technique allows for noncontact 3D characterization of hidden corrosion from a far distance to the structure. Finally, we believe this work will inspire new 3D damage quantification methods that are based on wavefield analysis as well as enable potential applications for the quantification of hidden corrosion in civil, petrochemical, nuclear, and aerospace structures.

42 ENGINEERING↗

DOE OSTI2026

Rhythmic Mechanisms Governing CAM Photosynthesis in Kalanchoe fedtschenkoi : High-Resolution Temporal Transcriptomics

Crassulacean acid metabolism (CAM) is a specialized photosynthetic pathway that enhances water-use efficiency by temporally separating nocturnal CO 2 uptake from daytime decarboxylation and carbon fixation. To uncover the regulatory mechanisms coordinating these temporal dynamics, we generated high-resolution, 48 h time-course transcriptomes for the CAM model Kalanchoe fedtschenkoi under both 12 h/12 h light/dark (LD) cycles and continuous light (LL). A rhythmicity analysis revealed that diel light cues are the dominant driver of transcript oscillations: 16,810 genes (54.3% of annotated genes) exhibited rhythmic expression only under LD, whereas just 399 genes (1.3%) remained rhythmic under LL. A smaller set of 3009 genes (9.7%) oscillated in both conditions, indicating that the intrinsic circadian clock sustains rhythmicity for a limited subset of the transcriptome. A gene co-expression network analysis revealed extensive integration between circadian clock components, core CAM pathway enzymes, and stomatal regulators, defining regulatory modules that coordinate metabolic and physiological timing. Notably, key hub genes associated with post-translational and post-transcriptional regulation, including the E3 ubiquitin ligase HUB2 and several pentatricopeptide repeat (PPR) proteins, act as central nodes in CAM-associated networks. This discovery implicates epigenetic and organellar regulation as previously unrecognized critical tiers of control in CAM. Together, our results support a regulatory model in which CAM rhythmicity is governed by both external light/dark cues and the endogenous circadian clock through multi-level control spanning transcriptional and protein-level regulation. To support community exploration, we also provide an interactive eFP (electronic Fluorescent Pictograph) browser for visualizing time-resolved gene expression profiles.

09 BIOMASS FUELS↗