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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Oculometric Biomarkers of Visuomotor Deficits in Clinically Asymptomatic Patients With Systemic Lupus Erythematosus Undergoing Long-Term Hydroxychloroquine Treatment

Introduction: This study examines a set of oculomotor measurements, or “oculometric” biomarkers, as potential early indicators of visual and visuomotor deficits due to retinal toxicity in asymptomatic Systemic Lupus Erythematosus (SLE) patients on long-term hydroxychloroquine (HCQ) treatment. The aim is to identify subclinical functional impairments that are otherwise undetectable by standard clinical tests and to link them to structural retinal changes. Methods: We measured oculomotor responses in a cohort of SLE patients on chronic HCQ therapy using a previously established behavioral task and analysis technique. We also examined the relationship between oculometrics, OCT measures of retinal thickness, and standard clinical perimetry measures of visual function in our patient group using Bivariate Pearson Correlation and a Linear Mixed-Effects Model (LMM). Results: Significant visual and visuomotor deficits were found in 12 asymptomatic SLE patients on long-term HCQ therapy compared to a cohort of 17 age-matched healthy controls. Notably, six oculometrics were significantly different. The median initial pursuit acceleration was 22%, steady-state pursuit gain 16%, proportion smooth 7%, and target speed responsiveness 31% lower, while catch-up saccade amplitude was 46% and fixation error 46% larger. Excluding the two patients with diagnosed mild toxicity, four oculometrics, all but fixation error and proportion smooth, remained significantly impaired compared to controls. Across our population of 12 patients (24 retinae), we found that pursuit latency, initial acceleration, steady-state gain, and fixation error were linearly related to retinal thickness even when age was accounted for, while standard measures of clinical function (Mean Deviation and Pattern Standard Deviation) were not. Discussion: Our data show that specific oculometrics are sensitive early biomarkers of functional deficits in SLE patients on HCQ that could be harnessed to assist in the early detection of HCQ-induced retinal toxicity and other visual pathologies, potentially providing early diagnostic value beyond standard visual field and OCT evaluations.

eye movements↗
NASA NTRS1982

The feasibility of thermal inertia mapping for detection of perched water tables in semi-arid irrigated lands

The thermal inertia mapping remote sensing technique is evaluated as a potential method for delineating areas of shallow perched water tables and related salinization problems on a regional basis. This method for detecting shallow water tables is based on the existence of significant differences in soil thermal properties between wet and dry soil profiles. Ground observations were conducted at two different test sites in California along the flight line, with one site located in a perched water table area and the other site in a well drained area. Measurements were taken hourly during a four day period (two days before and two days after the flight) for variables such as radiometric, meteorologic, soil moisture and temperature profiles, and surface characteristics. Results indicate that it is not feasible using present apparent thermal inertia remote sensing techniques to reliably delineate regional patterns of very shallow water tables due to the complex environmental system. However, some features within specific fields which may be directly related to the local presence of shallow water tables, such as differences in evaporative cooling due to soil moisture effects between and within fields, can be detected using the thermal inertia technique.

Ezra, C. E.↗
DOE OSTI2015

Spin Seebeck devices using local on-chip heating

A micro-patterned spin Seebeck device is fabricated using an on-chip heater. Current is driven through a Au heater layer electrically isolated from a bilayer consisting of Fe{sub 3}O{sub 4} (insulating ferrimagnet) and a spin detector layer. It is shown that through this method it is possible to measure the longitudinal spin Seebeck effect (SSE) for small area magnetic devices, equivalent to traditional macroscopic SSE experiments. Using a lock-in detection technique, it is possible to more sensitively characterize both the SSE and the anomalous Nernst effect (ANE), as well as the inverse spin Hall effect in various spin detector materials. By using the spin detector layer as a thermometer, we can obtain a value for the temperature gradient across the device. These results are well matched to values obtained through electromagnetic/thermal modeling of the device structure and with large area spin Seebeck measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Resolving molecular vibronic structure using high-sensitivity two-dimensional electronic spectroscopy

Coherent multidimensional optical spectroscopy is an emerging technique for resolving structure and ultrafast dynamics of molecules, proteins, semiconductors, and other materials. A current challenge is the quality of kinetics that are examined as a function of waiting time. Inspired by noise-suppression methods of transient absorption, here we incorporate shot-by-shot acquisitions and balanced detection into coherent multidimensional optical spectroscopy. We demonstrate that implementing noise-suppression methods in two-dimensional electronic spectroscopy not only improves the quality of features in individual spectra but also increases the sensitivity to ultrafast time-dependent changes in the spectral features. Measurements on cresyl violet perchlorate are consistent with the vibronic pattern predicted by theoretical models of a highly displaced harmonic oscillator. The noise-suppression methods should benefit research into coherent electronic dynamics, and they can be adapted to multidimensional spectroscopies across the infrared and ultraviolet frequency ranges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗
DOE OSTI2017

A historical survey of algorithms and hardware architectures for neural-inspired and neuromorphic computing applications

In this study, biological neural networks continue to inspire new developments in algorithms and microelectronic hardware to solve challenging data processing and classification problems. Here in this research, we survey the history of neural-inspired and neuromorphic computing in order to examine the complex and intertwined trajectories of the mathematical theory and hardware developed in this field. Early research focused on adapting existing hardware to emulate the pattern recognition capabilities of living organisms. Contributions from psychologists, mathematicians, engineers, neuroscientists, and other professions were crucial to maturing the field from narrowly-tailored demonstrations to more generalizable systems capable of addressing difficult problem classes such as object detection and speech recognition. Algorithms that leverage fundamental principles found in neuroscience such as hierarchical structure, temporal integration, and robustness to error have been developed, and some of these approaches are achieving world-leading performance on particular data classification tasks. Additionally, novel microelectronic hardware is being developed to perform logic and to serve as memory in neuromorphic computing systems with optimized system integration and improved energy efficiency. Key to such advancements was the incorporation of new discoveries in neuroscience research, the transition away from strict structural replication and towards the functional replication of neural systems, and the use of mathematical theory frameworks to guide algorithm and hardware developments.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

Control of air contaminants is a crucial factor in the safety considerations of crewed space flight. Indoor air quality needs to be closely monitored during long range missions such as a Mars mission, and also on large complex space structures such as the International Space Station. This work mainly pertains to the detection and simulation of air contaminants in the space station, though much of the work is easily extended to buildings, and issues of ventilation systems. Here we propose a method with which to track the presence of contaminants using an accurate physical model, and also develop a robust procedure that would raise alarms when certain tolerance levels are exceeded. A part of this research concerns the modeling of air flow inside a spacecraft, and the consequent dispersal pattern of contaminants. Our objective is to also monitor the contaminants on-line, so we develop a state estimation procedure that makes use of the measurements from a sensor system and determines an optimal estimate of the contamination in the system as a function of time and space. The real-time optimal estimates in turn are used to detect faults in the system and also offer diagnoses as to their sources. This work is concerned with the monitoring of air contaminants aboard future generation spacecraft and seeks to satisfy NASA's requirements as outlined in their Strategic Plan document (Technology Development Requirements, 1996).

Ramirez, W. Fred↗
DOE OSTI2015

Simulations for a next-generation UHECR observatory

We explore the potential of a future, ultra-high energy cosmic ray (UHECR) experiment, that is able to overcome the limitation of low statistics, to detect anisotropy in the arrival directions of UHECRs. We concentrate on the lower energy range of future instruments (E∼> 50 EeV), where, if the UHECR source number density is not too low, the sources should be numerous enough to imprint a clustering pattern in the sky, and thus possibly in the UHECR arrival directions. Under these limits, the anisotropy signal should be dominated by the clustering of astrophysical sources per se in the large-scale structures, and not the clustering of events around individual sources. We study the potential for a statistical discrimination between different astrophysical models which we parametrise by the number density of UHECR sources, the possible bias of the UHECR accelerators with respect to the galaxy distribution, and the unknown fraction of UHECRs that have been deflected by large angles. We demonstrate that an order-of-magnitude increase in statistics would allow to discriminate between a variety of astrophysical models, provided that a sub-sample of light elements can be extracted, and that it represents a fraction ∼> 70% of the overall flux, sensitive to the UHECR source number density. Discrimination should be possible even without knowledge of the composition of the UHECRs, as long as the data are proton-dominated. We find that an anisotropy at the 99.7% level should be detectable when the number of detected events exceeds 2000 beyond 50 EeV, as long as the composition is proton dominated, and the number density of UHECR sources is relatively high, n-bar ≥ 10{sup −3} Mpc{sup −3}. If the UHECR sources are strongly biased relative to the galaxy distribution, as are for example galaxy clusters, in which the sources might be embedded, an anisotropy at the 99.7% level should be detectable once the number of detected events exceeds 1000, if the fraction of protons at the highest energies is ∼> 60%.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

Open Circuit Resonant (SansEC) Sensor Technology for Lightning Mitigation and Damage Detection and Diagnosis for Composite Aircraft Applications

Traditional methods to protect composite aircraft from lightning strike damage rely on a conductive layer embedded on or within the surface of the aircraft composite skin. This method is effective at preventing major direct effect damage and minimizes indirect effects to aircraft systems from lightning strike attachment, but provides no additional benefit for the added parasitic weight from the conductive layer. When a known lightning strike occurs, the points of attachment and detachment on the aircraft surface are visually inspected and checked for damage by maintenance personnel to ensure continued safe flight operations. A new multi-functional lightning strike protection (LSP) method has been developed to provide aircraft lightning strike protection, damage detection and diagnosis for composite aircraft surfaces. The method incorporates a SansEC sensor array on the aircraft exterior surfaces forming a "Smart skin" surface for aircraft lightning zones certified to withstand strikes up to 100 kiloamperes peak current. SansEC sensors are open-circuit devices comprised of conductive trace spiral patterns sans (without) electrical connections. The SansEC sensor is an electromagnetic resonator having specific resonant parameters (frequency, amplitude, bandwidth & phase) which when electromagnetically coupled with a composite substrate will indicate the electrical impedance of the composite through a change in its resonant response. Any measureable shift in the resonant characteristics can be an indication of damage to the composite caused by a lightning strike or from other means. The SansEC sensor method is intended to diagnose damage for both in-situ health monitoring or ground inspections. In this paper, the theoretical mathematical framework is established for the use of open circuit sensors to perform damage detection and diagnosis on carbon fiber composites. Both computational and experimental analyses were conducted to validate this new method and system for aircraft composite damage detection and diagnosis. Experimental test results on seeded fault damage coupons and computational modeling simulation results are presented. This paper also presents the shielding effectiveness along with the lightning direct effect test results from several different SansEC LSP and baseline protected and unprotected carbon fiber reinforced polymer (CFRP) test panels struck at 40 and 100 kiloamperes following a universal common practice test procedure to enable damage comparisons between SansEC LSP configurations and common practice copper mesh LSP approaches. The SansEC test panels were mounted in a LSP test bed during the lightning test. Electrical, mechanical and thermal parameters were measured during lightning attachment and are presented with post test nondestructive inspection comparisons. The paper provides correlational results between the SansEC sensors computed electric field distribution and the location of the lightning attachment on the sensor trace and visual observations showing the SansEC sensor's affinity for dispersing the lightning attachment.

Szatkowski, George N.↗
DOE OSTI2025

When can we detect lianas from space? Toward a mechanistic understanding of liana‐infested forest optics

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Environmental Sciences & Ecology↗
DOE OSTI2015

Microstructure characterization of SiC nanowires as reinforcements in composites

SiC nanowires have been rarely investigated or explored along their axial direction by transmission electron microscopy (TEM). Here we report the investigation of the cross-section microstructure of SiC nanowires by embedding them into Al matrix. Morphology of SiC nanowires was cylindrical with smooth surface or bamboo shape. Cubic (3C-SiC) and hexagonal structure (2H-SiC) phases were detected by X-ray diffraction (XRD) analysis. High density stacking faults were observed in both the cylindrical and bamboo shaped nanowires which were perpendicular to their axial direction. Selected area electron diffraction (SAED) patterns of the cylindrical and bamboo shaped SiC nanowires both in the perpendicular and parallel direction to the axial direction were equivalent in the structure. After calculation and remodeling, it has been found that the SAED patterns were composed of two sets of diffraction patterns, corresponding to 2H-SiC and 3C-SiC, respectively. Therefore, it could be concluded that the SiC nanowires are composed of a large number of small fragments that are formed by hybrid 3C-SiC and 2H-SiC structures. - Graphical abstract: Display Omitted - Highlights: • Cross-section microstructure of SiC nanowires was observed in Al composite. • Cylindrical with smooth surface or bamboo shape SiC nanowires were found. • The cylindrical and bamboo shaped SiC nanowires were equivalent in structure. • Structure of SiC nanowires was remodeled. • SiC nanowires are composed of hybrid 3C-SiC and 2H-SiC structures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Absolute position measurement in a gas time projection chamber via transverse diffusion of drift charge

Time Projection Chambers (TPCs) with charge readout via micro pattern gaseous detectors can provide detailed measurements of charge density distributions. We here report on measurements of alpha particle tracks, using a TPC where the drift charge is amplified with Gas Electron Multipliers and detected with a pixel ASIC. We find that by measuring the 3-D topology of drift charge and fitting for its transverse diffusion, we obtain the absolute position of tracks in the drift direction. For example, we obtain a precision of 1~cm for 1~cm-long alpha track segments. To our knowledge this is the first demonstration of such a measurement in a gas TPC. This technique has several attractive features: it does not require knowledge of the initial specific ionization, is robust against bias from diffuse charge below detection threshold, and is also robust against high charge densities that saturate the detector response.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Degenerate domain walls in supersymmetric theories

In supersymmetric Yang–Mills theories tension-degenerate domain walls are typical. Adding matter fields in fundamental representation, we arrive at supersymmetric quantum chromodynamics (SQCD) supporting similar walls. We demonstrate that the degenerate domain walls can belong to one of two classes: i) locally distinguishable, i.e. those which differ from each other locally (which could be detected in local measurements); and ii) those which have identical local structure and are differentiated only topologically, through a judicially chosen compactification of R 4 . Depending on the number of flavors F and the pattern of Higgsing, both classes can coexist among SQCD k walls interpolating between the vacua n and n + k . We prove that the overall multiplicity of the domain walls obtained after accounting for both classes is ν N , k walls = N ! / [ ( N − k ) ! k ! ] , as was discovered previously in limiting cases. (Here, N is the number of colors.) Thus, ν N , k walls is a peculiar index. For the locally distinguishable degenerate domain walls, we observe two-wall junctions, a phenomenon specific for supersymmetry with central extensions. This phenomenon does not exist for topological replicas.

Chen, Shi↗
DOE OSTI2016

Problematic projection to the in-sample subspace for a kernelized anomaly detector

We examine the properties and performance of kernelized anomaly detectors, with an emphasis on the Mahalanobis-distance-based kernel RX (KRX) algorithm. Although the detector generally performs well for high-bandwidth Gaussian kernels, it exhibits problematic (in some cases, catastrophic) performance for distances that are large compared to the bandwidth. By comparing KRX to two other anomaly detectors, we can trace the problem to a projection in feature space, which arises when a pseudoinverse is used on the covariance matrix in that feature space. Here, we show that a regularized variant of KRX overcomes this difficulty and achieves superior performance over a wide range of bandwidths.

58 GEOSCIENCES↗
DOE OSTI2015

Metaproteomics Identifies the Protein Machinery Involved in Metal and Radionuclide Reduction in Subsurface Microbiomes and Elucidates Mechanisms and U(VI) Reduction Immobilization

The overall goal for this funded project was to develop and exploit environmental metaproteomics tools to identify biomarkers for monitoring microbial activity affecting U speciation at U-contaminated sites, correlate metaproteomics profiles with geochemical parameters and U(VI) reduction activity (or lack thereof), elucidate mechanisms contributing to U(VI) reduction, and provide remediation project managers with additional information to make science-based site management decisions for achieving cleanup goals more efficiently. Although significant progress has been made in elucidating the microbiology contribution to metal and radionuclide reduction, the cellular components, pathway(s), and mechanisms involved in U trans-formation remain poorly understood. Recent advances in (meta)proteomics technology enable detailed studies of complex samples, including environmental samples, which differ between sites and even show considerable variability within the same site (e.g., the Oak Ridge IFRC site). Additionally, site-specific geochemical conditions affect microbial activity and function, suggesting generalized assessment and interpretations may not suffice. This research effort integrated current understanding of the microbiology and biochemistry of U(VI) reduction and capitalize on advances in proteomics technology made over the past few years. Field-related analyses used Oak Ridge IFRC field ground water samples from locations where slow-release substrate biostimulation has been implemented to accelerate in situ U(VI) reduction rates. Our overarching hypothesis was that the metabolic signature in environmental samples, as deciphered by the metaproteome measurements, would show a relationship with U(VI) reduction activity. Since metaproteomic and metagenomic characterizations were computationally challenging and time-consuming, we used a tiered approach that combines database mining, controlled laboratory studies, U(VI) reduction activity measurements, phylogenetic analyses, and gene expression studies to support the metaproteomics characterizations. Growth experiments of target microorganisms (Anaeromyxobacter, Shewanella, Geobacter) revealed tremendous respiratory versatility, as evidenced by the ability to utilize a range of electron donors (e.g. acetate, hydrogen, pyruvate, lactate, succinate, formate) and electron acceptors (e.g. nitrate, fumarate, halogenated phenols, ferric iron, nitrous oxide, etc.). In particular, the dissimilatory metabolic reduction of metals, including radionuclides, by target microorganisms spurred interest for in situ bioremediation of contaminated soils and sediments. Distinct c-type cytochrome expression patterns were observed in target microorganisms grown with the different electron acceptors. For each target microorganism, the core proteome covered almost all metabolic pathways represented by their corresponding pan-proteomes. Unique proteins were detected for each target microorganism, and their expression and possible functionalities were linked to specific growth conditions through proteomics measurements. Optimization of the proteomic tools included in-depth comprehensive metagenomic and metaproteomic analyses on a limited number of samples. The optimized metaproteomic analyses were then applied to Oak Ridge IFRC field samples from the slow-release substrate biostimulation. Metaproteomic analysis and pathway mapping results demonstrated the distinct effects of metal and non-metal growth conditions on the proteome expression. With these metaproteomic tools, we identified which previously hypothetical metabolic pathways were active during the analyzed time points of the slow release substrate biostimulation. Thus, we demonstrated the utility of these tools for site assessment, efficient implementation of bioremediation and long-term monitoring. This research of detailed protein analysis linked with metal reduction activity did (1) show that c-type cytochrome isoforms, previously associated with radionuclide reduction activity, are suitable biomarkers, (2) identify new biomarker targets for site assessment and bioremediation monitoring, and (3) provide new information about specific proteins and mechanisms involved in U(VI) reduction and immobilization. This expanded metagenomic and metaproteomic toolbox contributed to implementing science-driven site management with broad benefits to the DOE mission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vitrification of Hanford Tank Wastes for Condensate Recycle and Feed Composition Changeover Testing

During the vitrification of Hanford Site nuclear waste at the Waste Treatment and Immobilization Plant (WTP), which is a part of the safe and efficient retrieval, treatment, and disposal mission of the U.S. Department of Energy Office of River Protection, the offgas condensate generated from the waste-to-glass conversion is currently planned to be concentrated by evaporation in the Effluent Management Facility (EMF). This concentrated condensate can then be recycled back to the incoming waste and vitrified. To test the recycle process, an apparatus was designed and built to mimic the EMF evaporator and was then used to concentrate a volume of condensate produced during the vitrification of a sample of Hanford tank 241-AP-107 (referred to herein as AP-107) waste in a continuous laboratory-scale melter (CLSM). The concentrated condensate was added to an additional sample of AP-107 waste, to mimic one round of the recycle process, and the combined solution was vitrified, producing a second round of recycle condensate. In the current study, the EMF test apparatus was used to concentrate the second-round recycle condensate under evaporation conditions (at 45 °C and 1.4 psia) designed to emulate EMF operation. The condensate was successfully concentrated by a factor of ~10 while retaining over 95 % of the technetium-99 ( 99 Tc), Cs, and I inventories in the concentrate. Another portion of AP-107 waste was retrieved by Washington River Protection Solutions, LLC (WRPS) and transferred to Pacific Northwest National Laboratory (PNNL), where it was pretreated and then combined with the second-round recycle AP-107 condensate concentrate and glass-forming chemicals (GFCs) to form the two-time recycle AP-107 melter feed, approximating a second round to the recycling action to be performed at the WTP. A portion of AP-105 waste was also retrieved by WRPS and provided to PNNL for pretreatment and combining with GFCs to form AP-105 melter feed. The two-time recycle AP-107 and AP-105 melter feeds were processed consecutively in the CLSM. The CLSM run proceeded for 13.63 hours, producing 9.70 kg of glass for an average glass production rate of 1464 kg m 2 d -1 during the two-time recycle AP-107 feed charging and 1568 kg m 2 d -1 during the AP-105 feed charging. The rate during AP-107 charging was essentially equivalent to the rate when processing no-recycle AP-107 feed and lower than that achieved when processing one-time recycle AP-107 feed. However, all rates were within the potential range of variability when processing melter feeds with similar composition in the CLSM. Likewise, the rate during AP-105 charging was higher than the previous rate processing AP-105, but within the potential CLSM range. The cold-cap characteristics changed from the typically thin AP-107 cold cap to a foamy-edged cold cap as previously seen with AP-105 shortly after transitioning to the AP-105 melter feed. The glass produced during the CLSM run was within 10 % of its target composition for the primary glass components. The CaO and Li 2 O targets varied by more than 1 wt% between the two-time recycle AP-107 and AP-105 glass targets and it took about 2 turnovers of the CLSM glass inventory to reach a relative chemical steady state in the glass for CaO and Li 2 O after the melter feed inputs were switched. The 99 Tc and total cesium content in the melter feeds were maintained at concentrations expected to be experienced at the WTP. During the CLSM run, while processing the two-time recycle AP-107 melter feed at a relative chemical steady state, the 99 Tc/Cs ratio was 10, and 34% of 99 Tc and 74% of Cs were retained in the glass. These values were higher than those measured in the CLSM run with one-time recycle AP-107 melter feed. After the transition to processing the AP-105 melter feed, when the production reached a relative chemical steady state, the 99 Tc/Cs ratio was 77 while 44% of 99 Tc was retained in the glass. The C's retention during this time frame reached 200% due to the excess C's in the glass after the target content decreased to 15% of its initial level in the two-time recycle AP-107 melter feed to the lower target in the Ap-105 melter feed. While iodine was below inductively coupled plasma mass spectrometry analytical reporting limits in the melter feed and glass samples, it was detected in quantities above the analytical reporting limits in the liquid and filter samples collected from the CLSM offgas treatment system. The behavior of iodine in the CLSM offgas treatment system followed a similar pattern to those of 99 Tc and Cs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
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↗
NASA NTRS1974

Feasibility study for locating archaeological village sites by satellite remote sensing techniques

The author has identified the following significant results. The objective is to determine the feasibility of detecting large Alaskan archaeological sites by satellite remote sensing techniques and mapping such sites. The approach used is to develop digital multispectral signatures of dominant surface features including vegetation, exposed soils and rock, hydrological patterns and known archaeological sites. ERTS-1 scenes are then printed out digitally in a map-like array with a letter reflecting the most appropriate classification representing each pixel. Preliminary signatures were developed and tested. It was determined that there was a need to tighten up the archaeological site signature by developing accurate signatures for all naturally-occurring vegetation and surface conditions in the vicinity of the test area. These second generation signatures have been tested by means of computer printouts and classified tape displays on the University of Alaska CDU-200 and by comparison with aerial photography. It has been concluded that the archaeological signatures now in use are as good as can be developed. Plans are to print out signatures for the entire test area and locate on topographic maps the likely locations of archaeological sites within the test area.

Cook, J. P.↗