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At least 199 records · Page 11

Measurements of stratospheric odd nitrogen at Arrival Heights, Antarctica, in 1991

An FTIR spectrometer was installed at Arrival Heights, Antarctica (78 deg S, 167 deg E) in February 1991 to measure the evolution of stratospheric HNO3 during the year. In particular, it was the intention to make the first observations of HNO3 trends during autumn, concurrently with ongoing measurements of column NO2 made with a grating spectrometer. The time-series of NO2 in the Antarctic shows a rapid decline in the column amount during autumn, and a slow recovery in spring, as the photochemical conditions move the species to and from higher storage reservoirs. The new nitric acid data show for the first time that during autumn the vertical column increases from approximately 1.9 x 10(exp 16) molecule cm(exp -2) at day 30 to approximately 3.1 x 10(exp 16) molecule cm(exp -2) by day 100. When the sun returns in spring, it is found that the column amount has fallen to about half the value at the end of autumn. Spring amounts are variable, but as found in the data from previous years remain low inside the vortex. The autumn increase is attributed to the heterogeneous conversion of N2O5 to gas-phase HNO3 on background aerosols. Low nitric acid column amounts at the start of spring suggest that the HNO3 has moved from the gas to the condensed phase on polar stratospheric clouds with the advent of low temperatures during the polar night.

Keys, J. Gordon↗

Estimated SAGE II ozone mixing ratios in early 1993 and comparisons with Stratospheric Photochemistry, Aerosols and Dynamic Expedition measurements

An empirical time-series model for estimating ozone mixing ratios based on Stratospheric Aerosols and Gas Experiment II (SAGE II) monthly mean ozone data for the period October 1984 through June 1991 has been developed. The modeling results for ozone mixing ratios in the 10- to 30- km region in early months of 1993 are presented. In situ ozone profiles obtained by a dual-beam UV-absorption ozone photometer during the Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE) campaign, May 1-14, 1993, are compared with the model results. With the exception of two profiles at altitudes below 16 km, ozone mixing ratios derived by the model and measured by the ozone photometer are in relatively good agreement within their individual uncertainties. The identified discrepancies in the two profiles are discussed.

Yue, G. K.↗

Steps toward determination of the size and structure of the broad-line region in active galactic nuclei. 8: An intensive HST, IUE, and ground-based study of NGC 5548

We present the data and initial results from a combined HST/IUE/ground-based spectroscopic monitoring campaign on the Seyfert 1 galaxy NGC 5548 that was undertaken in order to address questions that require both higher temporal resolution and higher signal-to-noise ratios than were obtained in our previous multiwavelength monitoring of this galaxy in 1988-89. IUE spectra were obtained once every two days for a period of 74 days beginning on 14 March 1993. During the last 39 days of this campaign, spectroscopic observations were also made with the HST Faint Object Spectrograph (FOS) on a daily basis. Ground-based observations, consisting of 165 optical spectra and 77 photometric observations (both CCD imaging and aperture photometry), are reported for the period 1992 October to 1993 September, although much of the data are concentrated around the time of the satellite-based program. These data constitute a fifth year of intensive optical monitoring of this galaxy. In this contribution, we describe the acquisition and reduction of all of the satellite and ground-based data obtained in this program. We describe in detail various photometric problems with the FOS and explain how we identified and corrected for various anomalies. During the HST portion of the monitoring campaign, the 1350 A continuum flux is found to have varied by nearly a factor of two. In other wavebands, the continuum shows nearly identical behavior, except that the amplitude of variability is larger at shorter wavelengths, and the continuum light curves appear to show more short time-scale variability at shorter wavelengths. The broad emission lines also vary in flux, with amplitudes that are slightly smaller than the UV continuum variations and with a small time delay relative to the UV continuum. On the basis of simple time-series analysis of the UV and optical continuum and emission line light curves, we find (1) that the ultraviolet and optical continuum variations are virtually simultaneous, with any lag between the 1350 A continuum and the 5100 A continuum amounting to less than about one day; (2) that the variations in the highest ionization lines observed, He II lambda 1640 and N V lambda 1240, lag behind the continuum variations by somewhat less than 2 days, and (3) that the velocity field of the C IV-emitting region is not dominated by radial motion. The results on the C IV velocity field are preliminary and quite uncertain, but there are some weak indications that the emission-line (wings absolute value of Delta upsilon is greater than or equal to 3000 km/s) respond to continuum variations slightly more rapidly than does the core. The optical observations show that the variations in the broad H beta line flux follow the continuum variations with a time lag of around two weeks, about twice the lag for Ly alpha and C IV, as in our previous monitoring campaign on this same galaxy. However, the lags measured for Ly alpha, C IV, and H Beta are each slightly smaller than previously determined. We confirm two trends reported earlier, namely (1) that the UV/optical continuum becomes 'harder' as it gets brighter, and (2) that the highest ionization emission lines have the shortest lags, thus indicating radial ionization stratificatin of a broad-line region that spans over an order of magnitude range in radius.

Korista, K.↗

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that the authors' techniques allow more accurate estimation of the global system loading, resulting in fewer object migrations than local methods. The authors' method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive load-balancing methods. Results from a preliminary analysis of another system and from simulation with a synthetic load provide some evidence of more general applicability.

LOAD CONTROL↗

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.

REAL TIME↗

Autonomic Responses to Microgravity

The purpose of this report is to describe how changes in autonomic nervous system responses may be used as an index of individual differences in adaptational capacity to space flight. During two separate Spacelab missions, six crewmembers wore an ambulatory monitoring system which enabled continuous recording of their physiological responses for up to twelve hours a day for 3 to 5 mission days. The responses recorded were electrocardiography, respiration wave form, skin conductance level, hand temperature, blood flow to the hands and triaxial accelerations of the head and upper body. Three of these subjects had been given training, before the mission, in voluntary control of these autonomic responses as a means of facilitating adaptation to space. Three of these subjects served as Controls, i.e., did not receive this training but took anti-motion sickness medication. Nearly 300 hours of flight data are summarized. These data were examined using time-series analyses, spectral analyses of heart rate variability, and analyses of variance. Information was obtained on responses to space motion sickness, inflight medications, circadian rhythm, workload and fatigue. Preliminary assessment was made on the effectiveness of self-regulation training as a means of facilitating adaptation, with recommendations for future flights.

Toscano, W. B.↗

Periodic extinction of families and genera

Eight major episodes of biological extinction of marine families over the past 250 million years stand significantly above local background (P < 0.05). These events are more pronounced when analyzed at the level of genus, and generic data exhibit additional apparent extinction events in the Aptian (Cretaceous) and Pliocene (Tertiary) Stages. Time-series analysis of these records strongly suggests a 26-million-year periodicity. This conclusion is robust even when adjusted for simultaneous testing of many trial periods. When the time series is limited to the four best-dated events (Cenomanian, Maestrichtian, upper Eocene, and middle Miocene), the hypothesis of randomness is also rejected for the 26-million-year period (P < 0.0002).

Non-NASA Center↗

(abstract) Mount Rainier: New Remote Sensing Observations of a Decade Volcano

Mount Rainier was selected as a Decade Volcano by the International Association of Volcanology and Chemistry of the Earth's Interior. The purpose of this selection is to focus scientific and public attention on Mount Rainier during the current decade, the United Nations-designated International Decade of Natural Hazard Reduction. The Mount Rainier science plan calls for remote sensing surveys to monitor the volcano. To date, we have conducted airborne surveys with visible and near-infrared, thermal infrared, and interferometric radar instruments. Our preliminary analysis of some night-time time-series thermal infrared survey data sets of the summit suggests that, aside from seasonal variations in snow cover, there have been no qualitative changes in the size or pattern of the summit hot spots. Day-time airborne surveys were done to record the current surface appearance of the volcano and map hydrothermal alteration in the summit region. An interferometric radar survey yielded a high-resolution digital elevation model (DEM) which serves as a base for the registration of the other remote sensing data sets. More importantly, the DEM documents the current topography of glaciers and valleys. Planned biannual radar survey of mount rainier will produce a data set from which seasonal changes in glacier and valley topography can be characterized. Such characterization is essential if we are to recognize geothermally induced changes in snow and ice cover.

infrared radar interferometry glaciers seasonal va↗

Satellite Microwave Radar- and Buoy-tracked Ice Motion in the Weddell Sea during WWGS '92

The first results of ERS-1 SAR sea-ice drift tracking are presented for Antarctica. Summer and winter examples illustrate temporal variations in ice drift in the Western and Eastern Weddell Sea during two field experiments. Time-series of mean drift velocity, divergence and rotation are compared with meteorological data from an ice camp and by instrumented buoys. Results indicate that SAR successfully characterizes the.

sea-ice ice formation Weddell Sea↗

AI-Enabled Operations at Fermi Complex: Multivariate Time Series Prediction for Outage Prediction and Diagnosis

The Main Control Room of the Fermilab accelerator complex continuously gathers extensive time-series data from thousands of sensors monitoring the beam. However, unplanned events such as trips or voltage fluctuations often result in beam outages, causing operational downtime. This downtime not only consumes operator effort in diagnosing and addressing the issue but also leads to unnecessary energy consumption by idle machines awaiting beam restoration. The current threshold-based alarm system is reactive and faces challenges including frequent false alarms and inconsistent outage-cause labeling. To address these limitations, we propose an AI-enabled framework that leverages predictive analytics and automated labeling. Using data from $2,703$ Linac devices and $80$ operator-labeled outages, we evaluate state-of-the-art deep learning architectures, including recurrent, attention-based, and linear models, for beam outage prediction. Additionally, we assess a Random Forest-based labeling system for providing consistent, confidence-scored outage annotations. Our findings highlight the strengths and weaknesses of these architectures for beam outage prediction and identify critical gaps that must be addressed to fully harness AI for transitioning downtime handling from reactive to predictive, ultimately reducing downtime and improving decision-making in accelerator management.

Jain, Milan [PNL, Richland] (ORCID:000000021676111↗

A Dynamic Hierarchical Attention Framework for Multimodal Malware Detection

The increasing use of Android in the worldwide mobile ecosystem has come along with a significant increase in advanced malware, highlighting the critical necessity for efficient, scalable, and adaptable detection systems. Despite recent advancements in machine learning improving malware detection, the majority of current solutions are limited to one, two, or three data modalities, hence neglecting the comprehensive behavioral spectrum of contemporary multi-vector threats. This thesis presents the first comprehensive multimodal framework for Android malware detection, which combines textual, time-series (temporal), graph-based (structural), and visual information using an innovative hierarchical attention mechanism and Dynamic Fusion Controller (DFC). Our methodology consistently classifies and processes modalities as either sequential or structural, facilitating content-adaptive weighting and resilient cross-modal representation learning. We advance the implementation of cutting-edge time series techniques, such as MiniRocket, for malware detection, hence creating new opportunities for temporal analysis in cybersecurity. Comprehensive experimental assessment shows that our framework performs exceptionally well, with 99.46% classification accuracy and 97.15% detection accuracy, significantly outperforming existing approaches through effective multimodal integration and hierarchical attention mechanisms.

Nazmin, Tamanna↗

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Extended abstract for Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗

The South Pole Telescope AGN Monitoring Campaign: First Release of SPTpol Bright AGN Light Curves

The South Pole Telescope (SPT) collaboration has recently embarked upon a campaign to monitor the brightness of a sample of active galactic nuclei (AGN), both in real time and in archival SPT data. The original design of the SPT was optimized for observations of the cosmic microwave background (CMB) at arc-minute and larger angular scales, and it has been used for this purpose for nearly twenty years, using three generations of CMB cameras. Recently it has been recognized that data from CMB experiments have the potential to be used for AGN monitoring. In this paper, we present the first public release of data from a full sample of SPT-monitored AGN, comprising 158 AGN light curves and associated data from the SPTpol camera, which was operational from 2012-2016. These light curves were created using observations from the SPTpol 500 deg$^{2}$ survey, in which the instrument was used to scan a 500 deg$^2$ patch of the sky several times per day with detectors sensitive to radiation in bands centered at 90 and 150 GHz. We provide a comprehensive description of the observations, the data processing methods, and the resulting light curve catalog. As an example of analyses that these data enable, we searched for a correlation between variability and spectral index, and we looked for ``bluer-when-brighter'' trends in the sample. Our analysis finds $> 10 σ$ correlation between fractional intrinsic variance and mean spectral index in the sample, but no significant evidence for bluer-when-brighter trends. The datasets from this study can be accessed through the SPT Treasury Record of AGN With Historical Activity and Time-Series or STRAWHAT catalog. This initial data release includes SPTpol light curves at 90 and 150 GHz, focusing on total intensity. In later updates, SPTpol polarization data and new observations from the SPT-3G instrument at 90, 150, and 220 GHz will be included.

Hood, J.C., II [Chicago U., KICP; Chicago U., Astr↗

Integrating Immersive Visualization in Molten-Salt Reactor Waste Management for Experimental Design and Planning

Molten-salt reactors (MSRs) represent a promising solution for next-generation nuclear energy, offering advantages in safety, fuel efficiency, and waste minimization. However, their liquid-fueled design presents unique challenges for spent fuel management, making post-shutdown waste characterization essential for developing effective strategies. Despite this need, there is a notable absence of visualization platforms specifically tailored to the unique characteristics and analytical requirements of MSR waste management. Existing tools in the nuclear industry are primarily designed for reactor operations or generic data exploration and lack both integration with MSR-specific multiphysics frameworks and the ability to simultaneously visualize time-dependent thermal fields, chemical composition evolution, and radiation distribution patterns. To address these limitations, this paper presents an immersive virtual reality (VR) visualization platform that processes and displays high-fidelity multiphysics simulation output from the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework in real-time, using Unity. The platform visualizes MSR waste characteristics such as nuclide decay, salt cooling, and corrosion by using Exodus II output data and running on a VR headset. It includes a user-friendly interface with features such as visibility toggling, cross-sectional slicing, and time-series animation for exploring simulation data. These capabilities support experimental design, stakeholder engagement, and public communication by making complex reactor behavior more accessible and understandable. By enhancing spatial reasoning and reducing cognitive load, this immersive environment fosters more effective communication and decision-making in MSR waste management.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Measurement-informed Dynamic Aggregation of Distribution Systems

This paper proposes a measurement-informed dynamic aggregation methodology in order to create equivalent representations of distribution systems that are compatible with large-scale transmission analysis. By optimizing an equivalent feeder parameters using time-series measurements of active power, reactive power, and voltage at the Point of Interconnection (POI), the approach yields simplified yet dynamically accurate equivalents. Implemented in PSCAD with models of photovoltaic–battery systems, three-phase motors, and static loads, the method employs hybrid differential evolution and bounded least-squares optimization laying the foundation for for real-time state estimation and optimized sensor placement in distribution networks.

Ahmed, Kazi Ishrak [University of Tennessee, Knoxv↗

Latency Analysis of the Nexus Digital Twin Framework

Real-time digital catalogs are increasingly relied upon to track metadata and connect disparate data sources for cloud-based data integration efforts. One such tool, Deeplynx Nexus is supporting real-time digital twin efforts through event-driven data integration and time-series queries. Nexus’s usefulness for these applications depends critically on how quickly individual records can be uploaded and downloaded, since delays directly affect the responsiveness of any system built on top of it. However, the actual latency a user should expect from Nexus has not been systematically measured before, particularly for the small, frequent transactions typical of live sensor feeds. Here we show that single-record round-trip latency is 61.1 ms on a local Nexus instance and 391.7 ms on the hosted production infrastructure, a roughly 6.4x difference driven primarily by fixed per-request overhead rather than data volume. This overhead dominates at small scale: comparing single-record and ten-record trials suggests approximately 56 ms of each single-record request is fixed connection and authentication cost rather than data-transfer time, meaning batching even a handful of records is substantially more efficient than transmitting them individually. At large batch sizes, this pattern reverses for uploads, which converge to near parity between local and hosted environments by 25,000-50,000 records, while download latency remains persistently 5.7-6.4x slower on hosted infrastructure even at scale. These results suggest that Nexus deployments intended for real-time digital twin applications should prioritize record batching over single-record transactions, and that download-path optimization on hosted infrastructure offers the largest remaining opportunity to reduce latency at scale. We anticipate these baseline measurements will serve as a reference point for future digital twin projects evaluating whether Nexus’s latency profile meets their real-time requirements, and as a benchmark for tracking the effect of future infrastructure or API changes.

99 - GENERAL AND MISCELLANEOUS↗

Evaluation of a generalized least squares algorithm for infrasound beamforming with coherent background noise

Infrasonic signals of interest can occur during periods with persistent, coherent, background noise, which may be natural or anthropogenic. For high signal-to-noise (SNR) ratio transient signals, an ‘overprinting’ of the coherent background may occur, and the signal may still be detected. However, this approach fails for low SNR signals of interest, which may be obscured by coherent noise. An infrasound beamforming method based on generalized least squares (GLS) is investigated for detecting transient signals of interest in the presence of coherent and incoherent background noise. This approach relies on an estimate of the noise covariance, captured in a covariance matrix, to effectively null contributions to the array response from noisy directions of arrival. Synthetic array data is used to investigate the performance of the GLS beamformer compared to the Bartlett beamformer when coherent and incoherent backgrounds are present. Additionally, the effects of array element number and relative strength of the interfering signal on the GLS estimates is investigated. GLS empirical area under the curve estimates suggest that the beamformer can recover coherent power for a signal of interest lower in amplitude than the coherent background, but this effectiveness degrades more quickly with SNR for a four element array compared to a six or eight element infrasound array. Finally, infrasound from the Forensic Surface Experiment, a bolide signal observed at IMS array I37NO, and a volcanic signal recorded at the Alaska Volcano Observatory array ADKI are used to evaluate GLS performance on recorded data. A ten minute window was used to capture the background noise, and the coherent background signal was nulled in all three examples.

58 GEOSCIENCES↗

Short-Term Forecasting of Thermostatic and Residential Loads Using Long Short-Term Memory Recurrent Neural Networks

Internet of Things (IoT) devices in smart grids enable intelligent energy management for grid managers and personalized energy services for consumers. Investigating a smart grid with IoT devices requires a simulation framework with IoT devices modeling. However, there lack comprehensive study on the modeling of IoT devices in smart grids. This paper investigates the IoT device modeling of a thermostatic load and implements the recurrent neural networks model for short-term load forecasting in this IoT-based thermostatic load. The recurrent neural network structure is leveraged to build a load forecasting model on temporal correlation. The temporal recurrent neural network layers including long short-term memory cells are employed to learn the data from both the simulation platform and New South Wales residential datasets. The simulation results are provided for demonstration.

electric load forecasting↗