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At least 1,387 records · Page 77

Capability Building Progression of an Insider Threat Mitigation Program at an International Research Reactor

The nuclear industry recognizes the difficulties involved in developing effective managerial and leadership skills in a highly technical and proficient workforce such as that found in nuclear facilities. Implementing an insider threat mitigation program (ITMP) within the nuclear industry is a complex and ongoing process that demands a comprehensive understanding of human behavior, an organization’s security culture, and rigorous regulatory requirements yet also accounts for facility characteristics, physical security, material flow, and activities involving nuclear material. Given the high-consequence nature of research reactor operations, even minor lapses can lead to safety, security, and reputational risks. An effective ITMP requires a defense-in-depth approach that incorporates behavioral analysis, robust vetting procedures, continuous monitoring, and cross-disciplinary coordination. It must also promote a culture of vigilance and accountability at all levels up to and including executive leadership but be flexible enough to adapt to evolving global threats and technological advances. Insider threat mitigation is not a one-time effort but rather a sustained commitment to excellence in safety and security. Establishing a culture in which personnel proactively report incidents and issues that could affect nuclear safety and security is vital to maintaining a safe and secure operational environment. This document was developed to guide senior management and research reactor organizations in creating comprehensive programs to effectively manage and mitigate insider threat behaviors and actions. It focuses on the key pillars of an effective ITMP, including the national legal framework, security culture, preventive and protective measures, cyber security, and performance evaluation. By using a systematic approach during implementation, facilities can foster environments conducive to insider threat detection and support long-term program sustainability. The document also provides strategies for improving communication across all levels of an organization, helping to eliminate barriers that hinder the development of robust ITMPs and enhance overall security culture. In today’s organizations, the concept of leveraging safety and security culture lessons to facilitate knowledge transfer is rapidly evolving to expedite insider threat management and security culture improvements. This document outlines the rationale for evaluating an ITMP based on national customs, culture, and stakeholders. The elements are all germane to reliability and trustworthiness and relate to security concerns that states may encounter. The document focuses not only on individual perceptions regarding security issues and capability building but also on team building and how to resolve concerns. The implementers of a facility’s ITMP may zero in on indicators of insider threats within their enterprise. This material will benefit organizations when it is applied using a systematic and structured approach as demonstrated throughout the document.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Jet charge modification in dense QCD matter

In these proceedings we report a recent calculation of the jet charge modification in heavy-ion relative to proton collisions at the LHC. Jets have played an essential role in constraining theories of in-medium parton shower evolution and in determining the properties of the quark-gluon plasma created in ultra-relativistic nuclear reactions. It is important to extend these studies to flavor-tagged jets and explore observables that are sensitive to their partonic origin. The average jet charge, introduced early on in the history of quantum chromodynamics, is a proxy for the electric charge of the quark or gluon that initiates the jet. In the framework of soft-collinear effective theory, we show how to evaluate the jet charge in a dense strongly-interacting matter environments. We identify observables that can isolate the contribution of in-medium branching from isospin effects and present predictions for the transverse momentum dependence of the jet charge distribution in nucleus-nucleus collisions and its modification relative to the proton case.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effective Field Theory of Random Quantum Circuits

Quantum circuits have been widely used as a platform to simulate generic quantum many-body systems. In particular, random quantum circuits provide a means to probe universal features of many-body quantum chaos and ergodicity. Some such features have already been experimentally demonstrated in noisy intermediate-scale quantum (NISQ) devices. On the theory side, properties of random quantum circuits have been studied on a case-by-case basis and for certain specific systems, and a hallmark of quantum chaos—universal Wigner–Dyson level statistics—has been derived. This work develops an effective field theory for a large class of random quantum circuits. The theory has the form of a replica sigma model and is similar to the low-energy approach to diffusion in disordered systems. The method is used to explicitly derive the universal random matrix behavior of a large family of random circuits. In particular, we rederive the Wigner–Dyson spectral statistics of the brickwork circuit model by Chan, De Luca, and Chalker [Phys. Rev. X 8, 041019 (2018)] and show within the same calculation that its various permutations and higher-dimensional generalizations preserve the universal level statistics. Finally, we use the replica sigma model framework to rederive the Weingarten calculus, which is a method of evaluating integrals of polynomials of matrix elements with respect to the Haar measure over compact groups and has many applications in the study of quantum circuits. The effective field theory derived here provides both a method to quantitatively characterize the quantum dynamics of random Floquet systems (e.g., calculating operator and entanglement spreading) and a path to understanding the general fundamental mechanism behind quantum chaos and thermalization in these systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US

Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (g A and T 0 ) in thermal remote-sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman–Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystem-scale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that integrates the Moderate Resolution Imaging Spectroradiometer (MODIS) derived TR and ancillary land surface variables in conjunction with NLDAS (North American Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth–Wallace (SW) framework for estimating ET at 1 km × 1 km spatial resolution. Evaluation of STIC1.2 at 13 core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66 % of the variability in observed 8-day cumulative ET with a root mean square error (RMSE) of 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/8-day, and percent bias (PBIAS) of -4 %. These error statistics showed relatively better accuracies than a widely used but previous version of the SEB-based Surface Energy Balance System (SEBS) model, which utilized a simple NDVI-based parameterization of surface roughness (z OM ), and the PM-based MOD16 ET. SEBS was found to overestimate (PBIAS = 28 %) and MOD16 was found to underestimate ET (PBIAS =-26 %). The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20 % underestimation) and woody savanna (40 % overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with g A and associated roughness length estimation uncertainties which are intrinsically connected to T R uncertainties, vapor pressure deficit (D A ), and vegetation cover. A consistent performance of STIC1.2 in a broad range of hydrological and biome categories, as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient, points to the potential for this simplified analytical model for near-real-time ET mapping from regional to continental scales.

Bhattarai, Nishan (ORCID:0000000327493549)↗

Contextualizing Data Streams for Infectious Disease Surveillance

To aid in developing a global biosurveillance program, it is critical to develop a framework to capture and understand the myriad of data streams and evaluate them in context of surveillance goals. Toward this goal, Los Alamos National Laboratory has developed a new method of evaluating the effectiveness of data stream types through the use of a novel concept called the surveillance window, a technique that integrates operational systems analysis, surveillance system analysis and epidemiological analysis. This study provides a simple, yet elegant methodology for which to ground truth known and emerging data streams for utility in integrated biosurveillance efforts.

59 BASIC BIOLOGICAL SCIENCES↗

FEMP Facility Evaluation (Audit) Decision Tree

This document is a resource to be used in concert with FEMP Audit Definitions, FEMP Consolidated Facility Management Guidance, and agency best practices and expert judgment—for agencies to use to determine the best approaches to evaluate their facilities. It features a decision tree that provides a framework for agencies to interpret gathered facility data to understand the existing conditions; benchmark the facility against others in the portfolio to determine whether an on-site or remote audit is appropriate for a facility; determine the best remote or on-site audit level of detail to meet agency facility auditing goals, such as meeting Energy Independence and Security Act of 2007 requirements and developing projects; and improve their energy and water management programs.

auditing↗

Making Data-Driven Policy Decisions for the Nation’s First Building Energy Performance Standards

Nearly every major U.S. city has committed itself to ambitious climate action goals – for Washington, DC this means a 50 percent reduction in greenhouse gases by 2032 and carbon neutrality by 2050. In support of these goals, Washington, DC has passed one of the most aggressive and practical climate action bills in the nation—with the Clean Energy DC Omnibus Act, DC became the first city in the U.S. to adopt energy performance standards for existing buildings. DC’s Building Energy Performance Standards (BEPS) require energy efficiency improvements for all commercial and multifamily buildings that do not meet a sector-specific minimum ENERGY STAR score or equivalent metric, with iterative compliance cycles every five years that will accelerate the pace of whole building retrofits. This paper explores this revolutionary policy framework and uses two data analysis projects that DC conducted to evaluate the potential impact of the BEPS and move towards carbon neutrality. First, we analyze the potential energy savings and greenhouse gas reductions, as well as potential cost impacts, from the implementation of a BEPS policy in DC We then examine the role of BEPS in a carbon neutrality strategy, how BEPS savings iterate over time, and what additional existing building improvements will be driven by the gravitational pull of new building codes on median performance. The paper highlights the benefits and limitations of such data-driven approaches to support policy decisions. Finally, we will review ongoing BEPS implementation, including expected policy directions, critical supportive programs, and lessons learned to date.

Bergfeld, Katie↗

Choosing Your Nuclear Fuel Cycle: A Life Cycle Assessment Perspective - 16425

Nuclear waste management has always been a much debated topic and a key driver for decisions within the nuclear industry. A standardised global approach has not yet been developed and at present many countries are re-considering their position. In the UK the reprocessing of Spent Nuclear Fuel is projected to stop, but no clear indication about the future approach has been given. This contribution sets out the early stages of an approach to compare the possible alternatives based on Life Cycle Assessment (LCA), which is widely used in other sectors to assess the overall environmental burdens of a product or a service across the whole life cycle - i.e. from cradle to grave. The LCA may serve to support decision-making processes within the nuclear industry and, provided that it is used in an open and transparent way, to improve public attitudes towards nuclear energy. To date few LCA studies within the nuclear industry have been carried out, the main issue being the lack of a standardised methodology to evaluate the impacts of radionuclides. The present study proposes a new framework for this purpose, and demonstrates its application in an LCA study of the current UK approach to the management of spent nuclear fuel based on specific data from plants at Sellafield. The final results of the study will show the overall environmental footprint of the reprocessing of spent nuclear fuel, in terms of both radiological and non-radiological impacts. A 'hot spot' analysis will also be performed to highlight the critical processing steps. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Developing IEEE Std 2800-Compliant Algorithms for Transmission-Connected Inverter-Based Resources: Preprint

This study addresses the compliance of Inverter-based Resources (IBRs) with the IEEE Std 2800, a leading standard that defines interconnection and interoperability requirements for IBRs integrated into transmission systems. Focusing on abnormal grid scenarios, the research evaluates the specific demands on IBRs, proposing a comprehensive controller development framework. This framework caters to maintaining ride-trhough operation or implementing strategic disconnections in line with IEEE Std 2800, alongside managing currents during voltage ride-through scenarios. The effectiveness of this proposed controller framework is rigorously validated through case studies, employing a MATLAB/Simulink model of an IBR to test its performance under diverse grid fault conditions, ensuring the IBRs' alignment with standard requirements and their robust performance in enhancing grid reliability.

IEEE Std 2800↗

Privacy-Aware RAG-Enabled LLMs for Collaborative AI in Organizations

Recent advancements in Large Language Models (LLMs) based on Transformer architectures have significantly improved capabilities in natural language processing and generation. However, deploying LLMs for inter-organizational communication poses challenges, in ensuring privacy and facilitating effective collaboration. This paper introduces a novel decentralized inference meta-agent chatbot that leverages privacy-aware Retrieval-Augmented Generation (RAG)-enabled LLMs for collaborative AI communication across organizations. Built on Microsoft’s Autogen, the platform enables LLMs to autonomously refine responses, enhancing accuracy and relevance. It incorporates advanced hallucination mitigation techniques using Uptrain and a privacy-focused RAG framework that employs synthetic document generation to protect sensitive information. Comprehensive evaluations demonstrate the platform’s effectiveness in maintaining contextual relevance and stringent privacy standards, effectively addressing critical challenges in LLM-enhanced collaborative AI communication. This work represents a significant step toward secure and efficient inter-organizational collaboration using advanced generative AI technologies.

97 - MATHEMATICS AND COMPUTING↗

Conditional Generative Adversarial Networks (cGANs) for Near Real-Time Precipitation Estimation from Multispectral GOES-16 Satellite Imageries—PERSIANN-cGAN

In this paper, we present a state-of-the-art precipitation estimation framework which leverages advances in satellite remote sensing as well as Deep Learning (DL). The framework takes advantage of the improvements in spatial, spectral and temporal resolutions of the Advanced Baseline Imager (ABI) onboard the GOES-16 platform along with elevation information to improve the precipitation estimates. The procedure begins by first deriving a Rain/No Rain (R/NR) binary mask through classification of the pixels and then applying regression to estimate the amount of rainfall for rainy pixels. A Fully Convolutional Network is used as a regressor to predict precipitation estimates. The network is trained using the non-saturating conditional Generative Adversarial Network (cGAN) and Mean Squared Error (MSE) loss terms to generate results that better learn the complex distribution of precipitation in the observed data. Common verification metrics such as Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), Bias, Correlation and MSE are used to evaluate the accuracy of both R/NR classification and real-valued precipitation estimates. Statistics and visualizations of the evaluation measures show improvements in the precipitation retrieval accuracy in the proposed framework compared to the baseline models trained using conventional MSE loss terms. This framework is proposed as an augmentation for PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network- Cloud Classification System) algorithm for estimating global precipitation.

42 ENGINEERING↗

Community size-spectra applied to recreational freshwater fisheries in Puerto Rican reservoirs

We developed a management framework based on community size-spectra (CSS) to establish targets to maximize desirable gamefish. We evaluated the influence of relative abundance of fish functional groups and watershed characteristics on the slope of the CSS or ecological efficiency. Both ecological efficiency and capacity were strongly influenced by relative abundance of fish functional groups and the degree of water level variation. Steeper slopes indicated overfished gamefish populations, whereas flatter slopes indicated systems dominated by undesirable invasive large-bodied low trophic position fish. We hypothesize that a desirable fishery would have a target range of CSS slopes that provides a deterministic community-based framework of predictable responses to environmental and food web changes that can be used to evaluate outcomes of management actions and a means to assess annual progress toward desirable conditions.

60 APPLIED LIFE SCIENCES↗

Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) is organizing the cooperation between the major nuclear data evaluation projects in the world. The NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established to promote the exchange of information on nuclear data evaluation, measurement, nuclear model calculation, validation, and related topics, and to provide a framework for cooperative activities between the participating projects. The working party assesses nuclear data improvement needs and addresses these needs by initiating joint activities in the framework of dedicated WPEC subgroups. Studies recently completed comprise a number of works related to nuclear data covariance and associated processing issues, as well as more specific studies related to the resonance parameter representation in the unresolved resonance region, the gamma production from fission-product capture reactions, the U-235 capture cross-section, the EXFOR database, and the improvement of nuclear data for advanced reactor systems. Ongoing activities focus on the evaluation of Pu-239 in the resonance region, scattering angular distribution in the fast energy range, and reporting/usage of experimental data for evaluation in the resolved resonance region. New activities include two new subgroups on improved fission product yield evaluation methodologies and on modern nuclear database structures. Future activities under discussion include a pilot project of a Collaborative International Evaluated Library (CIELO) and methods to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data. In addition to the above mentioned short-term, task-oriented subgroups, the WPEC also hosts a longer-term subgroup charged with reviewing and compiling the most important nuclear data requirements in a high priority request list (HPRL).

99 GENERAL AND MISCELLANEOUS↗

Numerical Simulation of Inter-basin Groundwater Flow into Northern Yucca Flat, Nevada National Security Site, Using the Death Valley Regional Flow System Model

Models of groundwater flow for the Yucca Flat area of the Nevada National Security Site (NNSS) are under development by the U.S. Department of Energy (DOE) for corrective action investigations of the Yucca Flat-Climax Mine Corrective Action Unit (CAU). One important aspect of these models is the quantity of inter-basin groundwater flow from regional systems to the north. This component of flow, together with its uncertainty, must be properly accounted for in the CAU flow models to provide a defensible regional framework for calculations of radionuclide transport that will support determinations of the Yucca Flat-Climax Mine contaminant boundary. Because characterizing flow boundary conditions in northern Yucca Flat requires evaluation to a higher level of detail than the scale of the Yucca Flat-Climax Mine CAU model can efficiently provide, a study more focused on this aspect of the model was required.

(CAU).↗

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation↗

The TENNLab Exploratory Neuromorphic Computing Framework

Spiking, neuromorphic computing systems are in a period of active exploration by the computing community. While they feature computational expressiveness beyond both von Neumann computing models and feed-forward neural networks, they are also challenging to design and program. The TENNLab exploratory neuromorphic computing framework is a software infrastructure, soon to be open-source, whose goal is to enable potential users of spiking, neuromorphic computing systems to develop applications and evaluate computing architectures, and for architecture researchers to develop and evaluate their architectures with a variety of applications. In this letter, we present the software architecture of the TENNLab framework.

97 MATHEMATICS AND COMPUTING↗

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim’s capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6 × better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware.

Vatsavai, Sairam Sri [Brookhaven National Laborato↗

A Consolidated Framework of the Color Variability in Blazars: Long-term Optical/Near-infrared Observations of 3C 279

We evaluate the optical/near-infrared (OIR) color variability of 3C 279 in both γ-ray flaring and non-flaring states over 7-year timescales using the Small and Medium Aperture Research Telescope System in Cerro Tololo, Chile and γ-ray fluxes obtained from the Fermi Gamma-ray Space Telescope. This observing strategy differs from previous blazar color variability studies in two key ways: (1) the reported color variability is assessed across optical through near-infrared wavelengths, and (2) the color variability is assessed over timescales significantly longer than an individual flare or ground-based observing season. We highlight 3C 279 because of its complex color variability, which is difficult to reconcile with the simple “redder-when-brighter” behavior often associated with Flat Spectrum Radio Quasar color variability. We suggest that the observed OIR color changes depend on a combination of the jet and disk emission. We parameterize this behavior in terms of a single variable, ζ{sub n}{sup m}, representing a smooth transition from a disk-dominated system, to a mixed contribution, to a jet-dominated system, which provides an explanation of the long-term OIR color variability in the same blazar over time. This suggests a general scheme that could apply to OIR color variability in other blazars.

79 ASTRONOMY AND ASTROPHYSICS↗