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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Detection and Characterization of Influenza A Virus Endemic Circulation in Suckling and Nursery Pigs Originating from Vaccinated Farms in the Same Production System

Inactivated influenza A virus (IAV) vaccines help reduce clinical disease in suckling piglets, although endemic infections still exist. The objective of this study was to evaluate the detection of IAV in suckling and nursery piglets from IAV-vaccinated sows from farms with endemic IAV infections. Eight nasal swab collections were obtained from 135 two-week-old suckling piglets from four farms every other week from March to September 2013. Oral fluid samples were collected from the same group of nursery piglets. IAV RNA was detected in 1.64% and 31.01% of individual nasal swabs and oral fluids, respectively. H1N2 was detected most often, with sporadic detection of H1N1 and H3N2. Whole-genome sequences of IAV isolated from suckling piglets revealed an H1 hemagglutinin (HA) from the 1B.2.2.2 clade and N2 neuraminidase (NA) from the 2002A clade. The internal gene constellation of the endemic H1N2 was TTTTPT with a pandemic lineage matrix. The HA gene had 97.59% and 97.52% nucleotide and amino acid identities, respectively, to the H1 1B.2.2.2 used in the farm-specific vaccine. A similar H1 1B.2.2.2 was detected in the downstream nursery. These data demonstrate the low frequency of IAV detection in suckling piglets and downstream nurseries from farms with endemic infections in spite of using farm-specific IAV vaccines in sows.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Self-Assembly of Accumulated Sphingolipids into Cytotoxic Fibrils in Globoid Cell Leukodystrophy and Their Inhibition by Small Molecules In Vitro

Globoid cell leukodystrophy (GLD) is a rare hereditary inborn error of metabolism due to recessive mutations that cause loss of function of the enzyme galactosylceramidase (GALC). This results in the accumulation of the sphingolipids galactosylceramide (GalCer) and galactosylsphingosine (GalSph) in the lysosomes of neuronal cells. The accumulated GalCer and GalSph in cerebral macrophages of GLD patients are neurotoxic to oligodendrocytes and Schwann cells, leading to demyelination in the nervous system. The disease typically presents with infantile onset in the first six months of life and death by age 2. Here, we identified a supramolecular structure of GalCer and GalSph that may contribute to GLD pathology. Using biophysical assays commonly used for studying proteinaceous amyloids, e.g., amyloidspecific dyes, microscopical imaging, and a series of analytical methods (FTIR, PXRD, and SAXS), we demonstrate that both GalCer and GalSph can self-assemble in vitro into highly organized fibrils reminiscent of fibrils of amyloidogenic proteins. These fibrils exhibit significant cytotoxicity to both neuronal and oligodendroglial cells. Using an inhibitor of the GALC enzyme in cell culture to mimic the GLD pathophysiology, we could detect the accumulation of these fibrils in cells. We also observed that small molecules, which are bona fide inhibitors of proteinaceous amyloids, effectively mitigated the formation of the GalCer and GalSph fibrillar structures in vitro. Finally, the small molecule ameliorated the cytotoxic effects of the sphingolipid fibrils in SH-SY5Y cells, suggesting a potential avenue for therapeutic intervention in GLD orphan disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Question-answering system extracts information on injection drug use from clinical notes

Background. Injection drug use (IDU) can increase mortality and morbidity. Therefore, identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no other structured data available, such as International Classification of Disease (ICD) codes, and IDU is most often documented in unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods. Here, to address this gap in clinical information, we design a question-answering (QA) framework to extract information on IDU from clinical notes for use in clinical operations. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We use 2323 clinical notes of 1145 patients curated from the US Department of Veterans Affairs (VA) Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information from temporally out-of-distribution data. Results. Here, we show that for a strict match between gold-standard and predicted answers, the QA model achieves a 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains a 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions. Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

AI-powered municipal solid waste management: a comprehensive review from generation to utilization

The accumulation of municipal solid waste (MSW) continues to rise due to burgeoning population, rapid global urbanization and economic growth, intensifying ecological concerns associated with landfills and greenhouse gas (GHG) emissions. Over the past 2 decades, global waste generation has surged by 50%, with one-third remaining uncollected and about 70% sent to landfills. This review examines the critical role of integrating emerging technologies, such as advanced sensors and artificial intelligence (AI), into end-to-end MSW management to alleviate landfill burdens. The suitability of various AI tools for different stages of MSW management is assessed, alongside the deployment of advanced sensors including hyperspectral cameras, computer vision systems, and internet of things (IoT) devices for material identification. Applications of genetic algorithms and reinforcement learning for optimizing collection routes, reducing costs, and lowering emissions are highlighted. Life cycle assessment (LCA) across all stages of MSW management is also reviewed, along with future trends in leveraging generative AI, natural language processing (NLP), and agent-based AI systems to analyze waste generation patterns and public sentiment. Efficient collection and handling can be enhanced through route optimization with geographic information systems and real-time bin-level monitoring. Furthermore, sensor-embedded, real-time object detection systems paired with robotics enable material characterization and automated sorting, thereby lowering costs and diverting waste from landfills into value-added products for diverse industrial sectors including packaging, chemicals, textiles, metals and glass, transportation, and electronics industries. Without intervention, global waste is projected to reach 4.54 billion tons by 2050, contributing direct economic costs of $\$$400 billion and roughly 2.38 billion tons of CO 2 -equivalent emissions annually. This review demonstrates how AI-driven, end-to-end solutions for MSW management can mitigate economic and environmental challenges, while directly supporting the United Nations Sustainable Development (UNDP) goals related to innovation and infrastructure (SDG 9), sustainable cities (SDG 11), responsible consumption and production (SDG 12), and climate action (SDG 13).

09 BIOMASS FUELS↗
DOE OSTI2024

Low-Cost and Portable Biosensor Based on Monitoring Impedance Changes in Aptamer-Functionalized Nanoporous Anodized Aluminum Oxide Membrane

We report a low-cost, portable biosensor composed of an aptamer-functionalized nanoporous anodic aluminum oxide (NAAO) membrane and a commercial microcontroller chip-based impedance reader suitable for electrochemical impedance spectroscopy (EIS)-based sensing. The biosensor consists of two chambers separated by an aptamer-functionalized NAAO membrane, and the impedance reader is utilized to monitor transmembrane impedance changes. The biosensor is utilized to detect amodiaquine molecules using an amodiaquine-binding aptamer (OR7)-functionalized membrane. The aptamer-functionalized membrane is exposed to different concentrations of amodiaquine molecules to characterize the sensitivity of the sensor response. The specificity of the sensor response is characterized by exposure to varying concentrations of chloroquine, which is similar in structure to amodiaquine but does not bind to the OR7 aptamer. A commercial potentiostat is also used to measure the sensor response for amodiaquine and chloroquine. The sensing response measured using both the portable impedance reader and the commercial potentiostat showed a similar dynamic response and detection threshold. The specific and sensitive sensing results for amodiaquine demonstrate the efficacy of the low-cost and portable biosensor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Genome integrity sensing by the broad-spectrum Hachiman antiphage defense complex

Hachiman is a broad-spectrum antiphage defense system of unknown function. We show here that Hachiman is a heterodimeric nuclease-helicase complex, HamAB. HamA, previously a protein of unknown function, is the effector nuclease. HamB is the sensor helicase. HamB constrains HamA activity during surveillance of intact double-stranded DNA (dsDNA). When the HamAB complex detects DNA damage, HamB helicase activity activates HamA, unleashing nuclease activity. Hachiman activation degrades all DNA in the cell, creating "phantom" cells devoid of both phage and host DNA. We demonstrate Hachiman activation in the absence of phage by treatment with DNA-damaging agents, suggesting that Hachiman responds to aberrant DNA states. Phylogenetic similarities between the Hachiman helicase and enzymes from eukaryotes and archaea suggest deep functional symmetries with other important helicases across domains of life.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Three‐trophic level food webs support the safety of a biocontrol agent 3 years after release

Biological control (biocontrol) is a powerful tool for managing invasive alien species and assisting the restoration of native ecosystems. Rigorous post‐release monitoring of biocontrol agents is critical to evaluate the success of biocontrol programs; however, this is still rarely implemented. Here, we combined the use of species interaction networks with a Before‐After Control‐Impact design to evaluate the target and non‐target, direct and indirect effects of the Australian gall wasp Trichilogaster acaciaelongifoliae , released to control the invasive plant Acacia longifolia in Portugal. We compared the structure of plant‐galling insect‐parasitoid food webs before and 3 years after the release of the biocontrol agent. Exhaustive sampling did not detect any non‐target effects, either direct (on non‐target plants) or indirect (on other galling insects via shared plants). Additionally, no significant changes were detected in network structure that could be related to the establishment of the biocontrol agent. This study shows that monitoring biocontrol at the community level is possible and that, when carefully planned, biocontrol poses minimal risk of non‐target effects.

López‐Núñez, Francisco A. [Centre for Functional E↗
DOE OSTI2025

Chlorine and potassium enrichment in the Cassiopeia A supernova remnant

The elements in the Universe are synthesized primarily in stars and supernovae, where nuclear fusion favours the production of even-Z elements. In contrast, odd-Z elements are less abundant and their yields are highly dependent on detailed stellar physics, making theoretical predictions of their cosmic abundance uncertain. In particular, the origin of odd-Z elements such as phosphorus (P), chlorine (Cl) and potassium (K), which are important for planet formation and life, is poorly understood. While the abundances of these elements in Milky Way stars are close to solar values, supernova explosion models systematically underestimate their production by up to an order of magnitude, indicating that key mechanisms for odd-Z nucleosynthesis are currently missing from theoretical models. Here we report the observation of P, Cl and K in the Cassiopeia A supernova remnant using high-resolution X-ray spectroscopy with X-Ray Imaging and Spectroscopy Mission data, with the detection of K at above the 6σ level being the most significant finding. Supernova explosion models of normal massive stars cannot explain the element abundance pattern, especially the high abundances of Cl and K, while models that include stellar rotation, binary interactions or shell mergers agree closely with the observations. Our observations suggest that such stellar activity plays an important role in supplying these elements to the Universe.

Astronomy and AstroPhysics↗
DOE OSTI2024

Designed 2D protein crystals as dynamic molecular gatekeepers for a solid-state device

The sensitivity and responsiveness of living cells to environmental changes are enabled by dynamic protein structures, inspiring efforts to construct artificial supramolecular protein assemblies. However, despite their sophisticated structures, designed protein assemblies have yet to be incorporated into macroscale devices for real-life applications. We report a 2D crystalline protein assembly of C98/E57/E66 L-rhamnulose-1-phosphate aldolase ( CEE RhuA) that selectively blocks or passes molecular species when exposed to a chemical trigger. CEE RhuA crystals are engineered via cobalt(II) coordination bonds to undergo a coherent conformational change from a closed state (pore dimensions <1 nm) to an ajar state (pore dimensions ~4 nm) when exposed to an HCN(g) trigger. When layered onto a mesoporous silicon (pSi) photonic crystal optical sensor configured to detect HCN (g) , the 2D CEE RhuA crystal layer effectively blocks interferents that would otherwise result in a false positive signal. The 2D CEE RhuA crystal layer opens in selective response to low-ppm levels of HCN (g) , allowing analyte penetration into the pSi sensor layer for detection. These findings illustrate that designed protein assemblies can function as dynamic components of solid-state devices in non-aqueous environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cross sections of 147–149 Sm( 6 Li,x) reactions for the production of 149 Tb for targeted alpha therapy

Terbium-149g (t 1/2 = 4.12 h) is of particular interest for targeted alpha therapy cancer treatment due to its ability to decay via both alpha and positron emission, making it a potential theranostic nuclide. Due to many challenges facing its production, there are limited facilities worldwide that have demonstrated the ability to produce this nuclide in quantities sufficient for medical research. Since the Cyclotron Institute at Texas A&M University is a specialized accelerator facility capable of accelerating a wide variety of ions, we are investigating production pathway options. One of the major challenges facing its production is the known co-production of the excited isomeric state, 149m Tb (t 1/2 = 4.1 min). However, this state does not decay to the ground state of 149g Tb, negating any potential contribution to its yield. Due to its short-half life, the cross section for the population of this state has never been measured. After calculating several potential reaction yields using predictive models, the reactions of 147–149 Sm( 6 Li,xn) 149 Tb were identified as candidates. Lithium-6 beams of varied energies between 45-65 MeV were impinged on enriched 147 Sm, 148 Sm, and 149 Sm targets at the Cyclotron Institute at Texas A&M University, and the reaction products were measured immediately following irradiation using high-purity germanium detectors, enabling detection of both 149m Tb and 149g Tb. Cross sections for all nuclides produced in sufficient activity in these reactions were also measured and reported here. We conclude that the population of 149m Tb is much preferred over population of the ground state for these 6 Li-induced reactions, and it is necessary to explore other options for 149g Tb production.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

A new method for quantifying 64 Cu in nuclear debris samples

Quantifying 64 Cu in post-detonation nuclear debris samples can provide important diagnostic information regarding the structural materials used within a nuclear device. However, this task is challenging due to the weak gamma emissions associated with the decay of 64 Cu, its short half-life (12.701 h), and the presence of interfering fission product radioisotopes. Large quantities of debris sample are generally needed to accurately quantify 64 Cu, which can be problematic in sample-limited scenarios where other radiometric analyses are required. Herein, we present a new method for the separation of 64 Cu from solutions of mixed fission products and demonstrate the quantification of its activity through use of gas-flow proportional beta counting. Here, the new method was validated through a series of rigorous tests and was shown to improve the detection limit of 64 Cu by over two orders of magnitude, from 2.5 × 10 6 to 1.3 × 10 4 atoms/sample for 100 min measurements.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Delamination of Multilayer Plastic Films to Recover Polyethylene with Favorable Mechanical Properties

Multilayer plastic films play a critical role in packaging, with each polymer layer contributing specific properties to the multilayer film. Multilayer plastic films are not currently recyclable due to the bound polymers. With multilayer film production of about 20 million metric tons in 2024 and rising, endof- life treatment becomes pressing. This work presents a scalable solvent-based delamination recycling process that is applied to commercial postindustrial multimaterial films to unbind the materials within a multilayer film by dissolving only the adhesive layer and recover polyethylene (PE) as an intact solid film. Solventbased delamination is a simple process that allows the complete recovery of materials and solvents used in the process. The delaminating solvent, 88% formic acid in water, induces delamination of PE/PEI/PET and PE/PU/PET films at 70 °C in under an hour. Recovered PE has no contamination detected by Fourier transform infrared spectroscopy and mechanical properties on par with those of virgin resin. The recovery of high-quality solid PE film fit for reprocessing, at low operating temperatures and with closed-loop solvent reuse, promotes delamination as a low energy consumption and environmentally friendly recycling process. PE recovered from delamination can be reused in equivalent products, promoting circularity of multimaterial films.

chemical recycling↗
DOE OSTI2024

Identification of equine mares as reservoir hosts for pathogenic species of Leptospira

Equine leptospirosis can result in abortion, stillbirth, neonatal death, placentitis, and uveitis. Horses can also act as subclinical reservoir hosts of infection, which are characterized as asymptomatic carriers that persistently excrete leptospires and transmit disease. In this study, PCR and culture were used to assess urinary shedding of pathogenic Leptospira from 37 asymptomatic mares. Three asymptomatic mares, designated as H2, H8, and H9, were PCR-positive for lipL32, a gene specific for pathogenic species of Leptospira. One asymptomatic mare, H9, was culture-positive, and the recovered isolate was classified as L. kirschneri serogroup Australis serovar Rushan. DNA capture and enrichment of Leptospira genomic DNA from PCR-positive, culture-negative samples determined that asymptomatic mare H8 was also shedding L. kirschneri serogroup Australis, whereas asymptomatic mare H2 was shedding L. interrogans serogroup Icterohaemorrhagiae. Sera from all asymptomatic mares were tested by the microscopic agglutination test (MAT) and 35 of 37 (94.6%) were seropositive with titers ranging from 1:100 to 1:3200. In contrast to asymptomatic mares, mare H44 presented with acute spontaneous abortion and a serum MAT titer of 1:102,400 to L. interrogans serogroup Pomona serovar Pomona. Comparison of L. kirschneri serogroup Australis strain H9 with that of L. interrogans serogroup Pomona strain H44 in the hamster model of leptospirosis corroborated differences in virulence of strains. Since lipopolysaccharide (LPS) is a protective antigen in bacterin vaccines, the LPS of strain H9 (associated with subclinical carriage) was compared with strain H44 (associated with spontaneous abortion). This revealed different LPS profiles and immunoreactivity with reference antisera. It is essential to know what species and serovars of Leptospira are circulating in equine populations to design efficacious vaccines and diagnostic tests. Our results demonstrate that horses in the US can act as reservoir hosts of leptospirosis and shed diverse pathogenic Leptospira species via urine. This report also details the detection of L. kirschneri serogroup Australis serovar Rushan, a species and serotype of Leptospira, not previously reported in the US.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Smart Planning for Radioactive Source Transport Advanced Tools for Increased Safety and Efficiency

End-of-life (EOL) management of high-activity radioactive sources is made uniquely challenging by the inherent risks associated with storage and transportation of these sources, the complex logistics involved, and the strict requirements for regulatory compliance. Traditional methods lack comprehensive tools for accurate site assessments and precision planning for the transportation of radioactive sources. They also frequently fail to provide the adaptability required to consider diverse operational environments, resulting in inefficiencies and potential safety concerns. This paper introduces a novel software solution developed to address these issues by integrating advanced technologies such as light detection and ranging (LiDAR)-based 3D environment modeling, smart dynamic route planning, and customizable measurement functionalities. This software enables detailed terrain visualizations, facilitating thorough environmental assessments and enabling users to virtually navigate, analyze, and plan site-specific operations. Among the key features are a user-centric interface for virtual navigation, precise site measurement tools for site evaluations, interactive visualizations that highlight potential operational hazards, dynamic route planning capabilities, and real-time collision detection to promote safe workflows. By demonstrating the effectiveness of this tool through real-world application, the present work underscores the tool’s potential to revolutionize radioactive source EOL management by improving operational efficiencies, minimizing risk, and advancing the state of practice to achieve suitable and secure radioactive material handling.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Organophosphorus nerve agents (OPNA) are hazardous environmental exposures to the civilian population and have been historically weaponized as chemical warfare agents (CWA). OPNA exposure can lead to several neurological, sensory, and motor symptoms that can manifest into chronic neurological illnesses later in life. There is still a large need for technological advancement to better understand changes in brain function following OPNA exposure. The human-relevant in vitro multi-electrode array (MEA) system, which combines the MEA technology with human stem cell technology, has the potential to monitor the acute, sub-chronic, and chronic consequences of OPNA exposure on brain activity. However, the application of this system to assess OPNA hazards and risks to human brain function remains to be investigated. In a concentration-response study, we have employed a human-relevant MEA system to monitor and detect changes in the electrical activity of engineered neural networks to increasing concentrations of the sarin surrogate 4-nitrophenyl isopropyl methylphosphonate (NIMP). We report a biphasic response in the spiking (but not bursting) activity of neurons exposed to low (i.e., 0.4 and 4 μM) versus high concentrations (i.e., 40 and 100 μM) of NIMP, which was monitored during the exposure period and up to 6 days post-exposure. Regardless of the NIMP concentration, at a network level, communication or coordination of neuronal activity decreased as early as 60 min and persisted at 24 h of NIMP exposure. Once NIMP was removed, coordinated activity was no different than control (0 μM of NIMP). Interestingly, only in the high concentration of NIMP did coordination of activity at a network level begin to decrease again at 2 days post-exposure and persisted on day 6 post-exposure. Notably, cell viability was not affected during or after NIMP exposure. Also, while the catalytic activity of AChE decreased during NIMP exposure, its activity recovered once NIMP was removed. Gene expression analysis suggests that human iPSC-derived neurons and primary human astrocytes resulted in altered genes related to the cell’s interaction with the extracellular environment, its intracellular calcium signaling pathways, and inflammation, which could have contributed to how neurons communicated at a network level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An expedited screening platform for the discovery of anti-ageing compounds in vitro and in vivo

Background: Restraining or slowing ageing hallmarks at the cellular level have been proposed as a route to increased organismal lifespan and healthspan. Consequently, there is great interest in anti-ageing drug discovery. However, this currently requires laborious and lengthy longevity analysis. Here, we present a novel screening readout for the expedited discovery of compounds that restrain ageing of cell populations in vitro and enable extension of in vivo lifespan. Methods: Using Illumina methylation arrays, we monitored DNA methylation changes accompanying long-term passaging of adult primary human cells in culture. This enabled us to develop, test, and validate the CellPopAge Clock, an epigenetic clock with underlying algorithm, unique among existing epigenetic clocks for its design to detect anti-ageing compounds in vitro. Additionally, we measured markers of senescence and performed longevity experiments in vivo in Drosophila, to further validate our approach to discover novel anti-ageing compounds. Finally, we bench mark our epigenetic clock with other available epigenetic clocks to consolidate its usefulness and specialisation for primary cells in culture. Results: We developed a novel epigenetic clock, the CellPopAge Clock, to accurately monitor the age of a population of adult human primary cells. We find that the CellPopAge Clock can detect decelerated passage-based ageing of human primary cells treated with rapamycin or trametinib, well-established longevity drugs. We then utilise the CellPopAge Clock as a screening tool for the identification of compounds which decelerate ageing of cell populations, uncovering novel anti-ageing drugs, torin2 and dactolisib (BEZ-235). We demonstrate that delayed epigenetic ageing in human primary cells treated with anti-ageing compounds is accompanied by a reduction in senescence and ageing biomarkers. Finally, we extend our screening platform in vivo by taking advantage of a specially formulated holidic medium for increased drug bioavailability in Drosophila. We show that the novel anti-ageing drugs, torin2 and dactolisib (BEZ-235), increase longevity in vivo. Conclusions: Our method expands the scope of CpG methylation profiling to accurately and rapidly detecting anti-ageing potential of drugs using human cells in vitro, and in vivo, providing a novel accelerated discovery platform to test sought after anti-ageing compounds and geroprotectors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Communication Network Layer State Estimation Measurement Model for a Cyber-Secure Smart Grid

Network communication has been proven to be a very important tool and a key factor in the recent development and progress of the power grid operation. It is also considered as the foundation for the smart grid because information and communication are integrated into electricity distribution to achieve reliable and accurate knowledge of the power grid. In previous years, absorbing energy from substations and delivering it to customers was the only type of interaction we knew between utility companies and customers. Presently, the growing connections of small distributed generation units caused by the cost reduction of most of the technologies used in generation and storage of electrical energy, along with the potential benefits of renewable energy have pushed many researchers to look into the improvement of information and communication technologies (ICT) in order to ensure a bidirectional flow of power and data. Moreover, the evolution of information and communication technologies and its applications to smart grid have converted the smart grid into a cyber-physical system where vulnerabilities and additional security challenges such as cyber-threats and cyber-attacks have emerged. Previously, we have demonstrated that using machine learning-based processing on data gathered from communication networks and the power grid was a promising solution for detecting cyber threats by implementing a co-simulation of cyber-security for cross-layer strategy. Since the majority of the challenges observed can only be solved in the network communication layer, we present in this work a physics-based state estimation model of the communication network system towards enhanced cyber-physical security of the smart grid. Information integration with the previously developed machine learning model is developed, providing a enhanced cyber-physical security application for the smart grid. Easy-to-implement model, without hard-to-derive parameters, highlight potential aspects of the model for real-life applications.

Mathieu, Reynold↗
DOE OSTI2026

A scalable variational method for estimating the latent infection-rate field of an outbreak

In this paper, we explore whether the infection-rate of a disease can serve as a robust monitoring variable in epidemiological surveillance algorithms. The infection-rate is dependent on population mixing patterns that do not vary erratically day-to-day; in contrast, daily case-counts used in contemporary surveillance algorithms are corrupted by reporting errors. The technical challenge lies in estimating the latent infection-rate from case-counts. Here we devise a Bayesian method to estimate the infection-rate across multiple adjoining areal units, and then use it, via an anomaly detector, to discern a change in epidemiological dynamics. We extend an existing model for estimating the infection-rate in an areal unit by incorporating a Markov random field model, so that we may estimate infection-rates across multiple areal units, while preserving spatial correlations observed in the epidemiological dynamics. To carry out the high-dimensional Bayesian inverse problem, we develop an implementation of mean-field variational inference specific to the infection model and integrate it with the random field model to incorporate correlations across counties. The method is tested on estimating the COVID-19 infection-rates across all 33 counties in New Mexico using data from the summer of 2020, and then employing them to detect the arrival of the Fall 2020 COVID-19 wave. We perform the detection using a temporal algorithm that is applied county-by-county. We also show how the infection-rate field can be used to cluster counties with similar epidemiological dynamics.

60 APPLIED LIFE SCIENCES↗