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Beyond universal behavior in the one-dimensional chain with random nearest-neighbor hopping

Here, we study the one-dimensional nearest-neighbor tight-binding model of electrons with independently distributed random hopping and no on-site potential (i.e., off-diagonal disorder with particle-hole symmetry, leading to sublattice symmetry, for each realization). For nonsingular distributions of the hopping, it is known that the model exhibits a universal, singular behavior of the density of states $ρ(E) ~ 1/|E\: \text{ln}^3 |E||$ and of the localization length $ξ(E) ~ |\text{ln}|E||$, near the band center $\textit{E}$ = 0 . (This singular behavior is also applicable to random $\textit{XY}$ and Heisenberg spin chains; it was first obtained by Dyson for a specific random harmonic oscillator chain.) Simultaneously, the state at$\textit{E}$ = 0 shows a universal, subexponential decay at large distances $\sim \text{exp}[–\sqrt{r/r_0}]$. In this study, we consider singular, but normalizable, distributions of hopping, whose behavior at small $\textit{t}$ is of the form $\sim 1/[t \text{ln}^{λ+1}(1/t)]$, characterized by a single, continuously tunable parameter λ > 0. We find, using a combination of analytic and numerical methods, that while the universal result applies for λ > 2, it no longer holds in the interval 0 < λ < 2. In particular, we find that the form of the density of states singularity is enhanced (relative to the Dyson result) in a continuous manner depending on the nonuniversal parameter λ; simultaneously, the localization length shows a less divergent form at low energies and ceases to diverge below λ = 1. For λ < 2, the fall-off of the $\textit{E}$ = 0 state at large distances also deviates from the universal result and is of the form $\sim\text{exp}[–(r/r_0)^{1/λ}]$ , which decays faster than an exponential for λ < 1.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integrating Heterogeneous Healthcare Datasets and Visual Analytics for Disease Bio-surveillance and Dynamics

n this paper, we present an overview of the big data chal- lenges in disease bio-surveillance and then discuss the use of visual analytics for integrating data and turning it into knowl- edge. We will explore two integration scenarios: (1) combining text and multimedia sources to improve situational awareness and (2) enhancing disease spread model data with real-time bio-surveillance data. Together, the proposed integration methodologies can improve awareness about when, where and how emerging diseases can affect wide geographic regions.

Ramanathan, Arvind↗

Interactive visual comparison of multimedia data through type-specific views

Analysts who work with collections of multimedia to perform information foraging understand how difficult it is to connect information across diverse sets of mixed media. The wealth of information from blogs, social media, and news sites often can provide actionable intelligence; however, many of the tools used on these sources of content are not capable of multimedia analysis because they only analyze a single media type. As such, analysts are taxed to keep a mental model of the relationships among each of the media types when generating the broader content picture. To address this need, we have developed Canopy, a novel visual analytic tool for analyzing multimedia. Canopy provides insight into the multimedia data relationships by exploiting the linkages found in text, images, and video co-occurring in the same document and across the collection. Canopy connects derived and explicit linkages and relationships through multiple connected visualizations to aid analysts in quickly summarizing, searching, and browsing collected information to explore relationships and align content. In this paper, we will discuss the features and capabilities of the Canopy system and walk through a scenario illustrating how this system might be used in an operational environment. Keywords: Multimedia (Image/Video/Music) Visualization.

Burtner, Edwin R.↗

Simple non-perturbative resummation schemes beyond mean-field II: Thermodynamics of scalar φ4 theory in 1 + 1 dimensions at arbitrary coupling

Recently, non-perturbative approximate solutions were presented that go beyond the well-known mean-field resummation. In this work, these non-perturbative approximations are used to calculate finite-temperature equilibrium properties for scalar [Formula: see text] theory in two dimensions such as the pressure, entropy density and speed of sound. Unlike traditional approaches, it is found that results are well-behaved for arbitrary temperature/coupling strength, are independent of the choice of the renormalization scale [Formula: see text], and are apparently converging as the resummation level is increased. Results also suggest the presence of a possible analytic cross-over from the high-temperature to the low-temperature regime based on the change in the thermal entropy density.

Astronomy & Astrophysics↗

Enhancing Clean Energy Innovation Ecosystem Discovery Tool

During March 2016, the DOE’s Office of Energy Policy and Systems Analysis (EPSA) sought a methodology to identify and quantify the strength of the existing clean energy innovation ecosystems (IE) in the U.S. and their characteristics. Oak Ridge National Lab (ORNL) did a pilot study (Phase 1) and demonstrated the feasibility of an application comprised of natural language processing, link analysis, and other computational techniques to transform text and numerical data into metrics on clean energy innovation activity and geography. The data-collection, ingest and analytics pipelines were combined with an advanced user interface, together known as the Ecosystem Discovery Tool, to enhance DOE’s understanding of existing geographic innovation clusters. During Phase 2 of this project, this tool has been further enhanced by integrating new data sets and through backend software architecture changes, validation and bug fixing, making it a much more robust and powerful application. The tool’s user interface is a lot more intuitive, which enables a user to visualize the IE rankings for various geographic regions(CBSA, state level) for different clean energy technologies and seek automated insights. ORNL also created a DOE-specific dashboard that allows the user to visualize and analyze federal funding from various offices including Energy Efficiency and Renewable Energy(EERE), Office of Electricity(OE), Fossil Energy(FE), and Nuclear Energy(NE). During Phase 1 of this project, EPSA defined a clean energy innovation ecosystem as the overlap of five Ecosystem Components: 1) nascent clean energy Indicators, 2) investors, 3) enabling environment, 4) networking assets and 5) large companies. EPSA and ORNL worked together to collect data for each component: 1) small and medium companies, ARPA-E awardees, SBIR awardees, patents, publications, ERCs for Nascent Clean Energy Indicators; 2) qualified investors; 3) the Clean Edge Policy Index/DSIRE for the Enabling Environment; 4) universities, national laboratories, ERCs and incubators for Networking Assets; and 5) large companies and a subset of the Russell 1000 list for Large Companies. The ORNL team created a visual tool based on Tableau that integrated ecosystem component data to score, rank and map IEs. The tool was created with the flexibility to allow the user to choose the weights of each of the five ecosystem components and the subcomponents. This flexibility allows the user to visualize different subsets and to use the underlying data for different types of analysis. During Phase 2 of this project, the backend database and computation process have undergone major changes to provide a much more refined user-interface and added new features into the scoring algorithm. This phase also involved addition of newer databases such as a list of Energy Research Centers (ERC) ,DSIRE, and funding data from EERE, FE, NE, and OE to provide more granular information and more accurate/better quantification.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Comprehensive Database of Environmental Mitigations Extracted from FERC-Licensed Hydropower Projects Using Artificial Intelligence Techniques, 1998-2023

This dataset provides a comprehensive inventory of environmental mitigation measures required by Federal Energy Regulatory Commission (FERC) licensed hydropower facilities from 461 licenses that were issued from 1998 to 2023. These licenses constitute 446 of the 1015 FERC projects that were active at the end of 2023. 17,612 mentions of environmental mitigations were identified and categorized in 128 unique categories. Mitigations were identified using a Natural Language Processing (NLP) approach, specifically with a Bidirectional Encoder Representations from Transformer (BERT) model. Model-derived results were then reviewed and updated by a subject matter expert as needed. This dataset introduces important enhancements to previous efforts to inventory environmental mitigations, such as including associated license text for each mitigation, tracking the number of instances a mitigation was identified within a license, and providing improved location information. These enhancements significantly expand the dataset's utility, offering greater analytical capabilities and ensuring reproducibility. The dataset is downloadable as a zip file containing the metadata and dataset files.

Ruggles, Thomas [Oak Ridge National Laboratory (OR↗

Data for Myers-Pigg et al. (2026), "Short-term coastal forest responses to a hurricane-scale freshwater and saltwater flooding experiment"

Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗

MAMA User Guide v2.0.1

Morphological signatures of bulk SNM materials have significant promise, but these potential signatures are not fully utilized. This document describes software tools, collectively called the MAMA (Morphological Analysis for Material Attribution) software that can help provide robust and accurate quantification of morphological features in bulk material microscopy images (Optical, SEM). Although many of the specific tools are not unique to Mama, the software package has been designed specifically for nuclear material morphological analysis, and is at a point where it can be easily adapted (by Los Alamos or by collaborators) in response to new, different, or changing forensics needs. The current release of the MAMA software only includes the image quantification, descriptions, and annotation functionality. Only limited information on a sample, its pedigree, and its chemistry are recorded inside this part of the software. This was decision based on initial feedback and the fact that there are several analytical chemistry databases being developed within the community. Currently MAMA is a standalone program that can export quantification results in a basic text format that can be imported into other programs such as Excel and Access. There is also a basic report generating feature that produces HTML formatted pages of the same information. We will be working with collaborators to provide better integration of MAMA into their particular systems, databases and workflows.

97 MATHEMATICS AND COMPUTING↗

Small body mass determination from a flyby

This paper investigates the accuracy with which the mass of a small body can be determined from a flyby. Due to the nearly linear nature of hyperbolic flybys of small bodies, analytic solutions can be derived. Four analytic solutions are developed, each of increasing complexity with different applications. These solutions are compared to a complex computer simulation for accuracy. When these methods are applied to nearly linear trajectories, the analytic solutions agree with the computer simulation results to within 4.0 percent except in one boundary case which is discussed in the text. Also described is the linear range for which these equations are applicable. These solutions are then applied to the proposed asteroid flyby of the CRAF mission to predict the mass estimate accuracy.

Sybert, Catherine B.↗

Buckling-induced interaction between circular inclusions in an infinite thin plate

Design of slender artificial materials and morphogenesis of thin biological tissues typically involve stimulation of isolated regions (inclusions) in the growing body. These inclusions apply internal stresses on their surrounding areas that are ultimately relaxed by out-of-plane deformation (buckling). Here, we utilize the Föppl-von Kármán model to analyze the interaction between two circular inclusions in an infinite plate that their centers are separated a distance of 2ℓ. In particular, we investigate a region in phase space where buckling occurs at a narrow transition layer of length ℓ D around the radius of the inclusion, $R (ℓ_D \ll R)$. We show that the latter length scale defines two regions within the system, the close separation region, $ℓ – R \sim ℓ_D$, where the transition layers of the two inclusions approximately coalesce, and the far separation region, $ℓ – R \gg ℓ_D$. While the interaction energy decays exponentially in the latter region, $E_{\text{int}} ∝ e^{– (ℓ – R)/ℓ_D}$, it presents nonmonotonic behavior in the former region. While this exponential decay is predicted by our analytical analysis and agrees with the numerical observations, the close separation region is treated only numerically. In particular, we utilize the numerical investigation to explore two different scenarios within the final configuration: The first where the two inclusions buckle in the same direction (up-up solution) and the second where the two inclusions buckle in opposite directions (up-down solution). We show that the up-down solution is always energetically favorable over the up-up solution. In addition, we point to a curious symmetry breaking within the up-down scenario; we show that this solution becomes asymmetric in the close separation region.

42 ENGINEERING↗

Measurement of toroidal vessel eddy current during plasma disruption on J-TEXT

In this paper, we have employed a thin, printed circuit board eddy current array in order to determine the radial distribution of the azimuthal component of the eddy current density at the surface of a steel plate. The eddy current in the steel plate can be calculated by analytical methods under the simplifying assumptions that the steel plate is infinitely large and the exciting current is of uniform distribution. The measurement on the steel plate shows that this method has high spatial resolution. Then, we extended this methodology to a toroidal geometry with the objective of determining the poloidal distribution of the toroidal component of the eddy current density associated with plasma disruption in a fusion reactor called J-TEXT. The preliminary measured result is consistent with the analysis and calculation results on the J-TEXT vacuum vessel.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NOUS: Construction and Querying of Dynamic Knowledge Graphs

The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a trans- formative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-to-end framework for developing custom knowl- edge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queries where the answer is embedded across multiple data sources.

Choudhury, Sutanay↗

EMP, Attachment 1: Sampling and Analysis Plan (Rev.1)

This Sampling and Analysis Plan (SAP) is written for the Environmental Radiation Task activities related to radioactive air emissions (stack) monitoring and environmental radiological ambient air surveillance of Pacific Northwest National Laboratory (PNNL) operations at the PNNL-Richland campus and PNNL-Sequim campus. PNNL is a U.S. Department of Energy Office of Science laboratory in Richland, Washington. This plan is an attachment to PNNL’s Environmental Radiological Air Monitoring Plan (EMP) (PNNL-20919) and addresses a discrete, vital subject area that is subject to revision independent of the main text of the EMP document. This SAP provides the requirements for planning sampling events and the requirements imposed on the services provided by the analytical laboratory to the PNNL Environmental Radiation Task.

40 CFR 61 Subpart H↗

Solubility Model for Ferrous Iron Hydroxide, Hibbingite, Siderite, and Chukanovite in High Saline Solutions of Sodium Chloride, Sodium Sulfate, and Sodium Carbonate

Here, a solubility model is presented for ferrous iron hydroxide (Fe(OH) 2 (s)), hibbingite (Fe 2 Cl(OH) 3 (s)), siderite (FeCO 3 (s)), and chukanovite (Fe 2 CO 3 (OH) 2 (s)). The Pitzer activity coefficient equation was utilized in developing the model to account for the excess free energies of aqueous species in the background solutions of high ionic strength. Solubility limiting minerals were analyzed before and after experiments using X-ray diffraction. Formation of Fe(OH) 2 (s) was observed in the experiments that were initiated with Fe 2 Cl(OH) 3 (s) in Na 2 SO 4 solution. Coexistence of siderite and chukanovite was observed in the experiments in Na 2 CO 3 + NaCl solutions. Two equilibrium constants that had been reported by us for the dissolution of Fe(OH) 2 (s) and Fe 2 Cl(OH) 3 (s) (Nemer et al.) were rederived in this paper, using newer thermodynamic data selected from the literature to maintain internal consistency of the series of our data analyses in preparation, including this paper. Three additional equilibrium constants for the following reactions were determined in this paper: dissolution of siderite and chukanovite and dissociation of the aqueous species Fe(CO 3 ) 2 –2 . Five Pitzer interaction parameters were derived in this paper: β (0) , β (1) , and C φ parameters for the species pair Fe +2 /SO 4 –2 ; β (0) and β (1) parameters for the species pair Na+/Fe(CO3)2–2. Our model predicts that, among the four inorganic ferrous iron minerals, siderite is the stable mineral in two WIPP-related brines (WIPP: Waste Isolation Pilot Plant), i.e., GWB and ERDA6 (Brush and Domski), and the electrochemical equilibrium between elemental iron and siderite provides a low oxygen fugacity (10 –91.2 atm) that can keep the actinides at their lowest oxidation states. (Nemer et al., Brush and Domski; references numbered 1 and 2 in the main text).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA Indexing Benchmarks: Evaluating Text Search Engines

The current proliferation of on-line information resources underscores the requirement for the ability to index collections of information and search and retrieve them in a convenient manner. This study develops criteria for analytically comparing the index and search engines and presents results for a number of freely available search engines. A product of this research is a toolkit capable of automatically indexing, searching, and extracting performance statistics from each of the focused search engines. This toolkit is highly configurable and has the ability to run these benchmark tests against other engines as well. Results demonstrate that the tested search engines can be grouped into two levels. Level one engines are efficient on small to medium sized data collections, but show weaknesses when used for collections 100MB or larger. Level two search engines are recommended for data collections up to and beyond 100MB.

Esler, Sandra L.↗

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Bryant, Cody↗

Large High Resolution Displays for Co-Located Collaborative Sensemaking: Display Usage and Territoriality

Large, high-resolution vertical displays carry the potential to increase the accuracy of collaborative sensemaking, given correctly designed visual analytics tools. From an exploratory user study using a fictional textual intelligence analysis task, we investigated how users interact with the display to construct spatial schemas and externalize information, as well as how they establish shared and private territories. We investigated the space management strategies of users partitioned by type of tool philosophy followed (visualization- or text-centric). We classified the types of territorial behavior exhibited in terms of how the users interacted with information on the display (integrated or independent workspaces). Next, we examined how territorial behavior impacted the common ground between the pairs of users. Finally, we offer design suggestions for building future co-located collaborative visual analytics tools specifically for use on large, high-resolution vertical displays.

co-located collaborative sensemaking↗

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗