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At least 289 records · Page 16

Magnetopause surface fluctuations observed by Voyager 1

Moving out of the dawnside of the earth's magnetosphere, Voyager 1 crossed the magnetopause apparently seven times, despite the high spacecraft speed of 11 km/sec. Normals to the magnetopause and their associated error cones were estimated for each of the crossings using a minimum variance analysis of the internal magnetic field. The oscillating nature of the ecliptic plane component of these normals indicates that most of the multiple crossings were due to a wave-like surface disturbance moving tailward along the magnetopause. The wave, which was aperiodic, was modeled as a sequence of sine waves. The amplitude, wavelength, and speed were determined for two pairs of intervals from the measured slopes, occurrence times, and relative positions of six magnetopause crossings. The magnetopause thickness was estimated to lie in the range 300 to 700 km with higher values possible. The estimated amplitude of these waves was obviously small compared to their wavelengths.

Lepping, R. P.↗

Quantifying Structural Relationships of Metal-Binding Sites Suggests Origins of Biological Electron Transfer

Biological redox reactions drive planetary biogeochemical cycles. Using a novel, structure-guided sequence analysis of proteins, we explored the patterns of evolution of enzymes responsible for these reactions. Our analysis reveals that the folds that bind transition metal–containing ligands have similar structural geometry and amino acid sequences across the full diversity of proteins. Similarity across folds reflects the availability of key transition metals over geological time and strongly suggests that transition metal–ligand binding had a small number of common peptide origins. We observe that structures central to our similarity network come primarily from oxidoreductases, suggesting that ancestral peptides may have also facilitated electron transfer reactions. Last, our results reveal that the earliest biologically functional peptides were likely available before the assembly of fully functional protein domains over 3.8 billion years ago. Thus, life is a special, very complex form of motion of matter, but this form did not always exist, and it is not separated from inorganic nature by an impassable abyss; rather, it arose from inorganic nature as a new property in the process of evolution of the world. We must study the history of this evolution if we want to solve the problem of the origin of life.

Yana Bromberg↗

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗

Study of time-lapse processing for dynamic hydrologic conditions

The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies.

Serebreny, S. M.↗

Microbial Characterization During the Early Habitation of the International Space Station

An evaluation of the microbiota from air, water, and surface samples provided a baseline of microbial characterization onboard the International Space Station (ISS) to gain insight into bacterial and fungal contamination during the initial stages of construction and habitation. Using 16S genetic sequencing and rep-PCR, 63 bacterial strains were isolated for identification and fingerprinted for microbial tracking. Of the bacterial strains that were isolated and fingerprinted, 19 displayed similarity to each other. The use of these molecular tools allowed for the identification of bacteria not previously identified using automated biochemical analysis and provided a clear indication of the source of several ISS contaminants. Strains of Bradyrhizobium and Sphingomonas unable to be identified using sequencing were identified by comparison of rep-PCR DNA fingerprints. Distinct DNA fingerprints for several strains of Methylobacterium provided a clear indication of the source of an ISS water supply contaminant. Fungal and bacterial data acquired during monitoring do not suggest there is a current microbial hazard to the spacecraft, nor does any trend indicate a potential health risk. Previous spacecraft environmental analysis indicated that microbial contamination will increase with time and will require continued surveillance. Copyright 2004 Springer-Verlag.

Fungi/genetics↗

Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization

The Sampler sequence was introduced into the SCALE nuclear modeling and simulation suite in SCALE 6.2 to perform uncertainty quantification via random sampling of nuclear data, material number densities, and dimensions. Sampler was expanded with the introduction of a parametric capability in SCALE 6.2.2. This paper discusses input for the Sampler parametric sequence and presents two case studies of analyses performed using the sequence. These case studies include preconceptual design of a package for transporting high assay low-enriched uranium (HALEU) oxide and scoping calculations to support subcritical limit development for a future update of the ANSI/ANS-8.1 (ANS-8.1) standard. The parametric capability within Sampler provides many benefits to analysts. For instance, parametric sweeps are frequently used to identify optimum parameter values as part of safety analysis or system design, but such sweeps can require substantial engineering time or may rely on custom-written scripts or scripts such as Write One, Run Many (or WORM) developed outside of any software quality assurance program. With the parametric capabilities in Sampler, however, a large number of inputs can be generated automatically without recourse to scripting by individual analysts. The parametric capability can also be used in lieu of the CSAS5S search sequence to identify optimum parameters more simply with straightforward inputs and outputs. Sampler can also be used to calculate input parameters from engineering specifications. For example, diameters can be converted to radii, or masses can be used to calculate number densities. Overall, the Sampler parametric capability provides a robust feature within SCALE, eliminating the need for user-developed scripting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analysis of seismic body waves excited by the Mount Saint Helens eruption of May 18, 1980

Seismic body waves which were excited by eruption of Mt. St. Helens, and recorded by the Global Digital Seismographic Network (GDSN) stations are analyzed to determine the nature and the time sequence of the events associated with the eruption. The polarity of teleseismic P waves (period 20 sec) is identical at six stations which are distributed over a wide azimuthal range. This observation, together with a very small S to P amplitude ratio (at 20 sec), suggests that the source is a nearly vertical single force that represents the counter force of the eruption. The time history of the vertical force suggests two distinct groups of events, about two minutes apart, each consisting of several subevents with a duration of about 25 sec. The magnitude of the force is approximately 2.6 to the 17th power dyne. this vertical force is in contrast with the long period (approximately 150 sec) southward horizontal single force which was determined by a previous study and interpreted to be due to the massive landslide.

Kanamori, H.↗

Analysis of seismic body waves excited by the Mount St. Helens eruption of May 18, 1980

Seismic body waves which were excited by eruption of Mt. St. Helens, and recorded by the Global Digital Seismographic Network (GDSN) stations are analyzed to determine the nature and the time sequence of the events associated with the eruption. The polarity of teleseismic P waves (period 20 sec) is identical at six stations which are distributed over a wide azimuthal range. This observation, together with a very small S to P amplitude ratio (at 20 sec), suggests that the source is a nearly vertical single force that represents the counter force of the eruption. The time history of the vertical force suggests two distinct groups of events, about two minutes apart, each consisting of several subevents with a duration of about 25 sec. The magnitude of the force is approximately 2.6 to the 17th power dyne. This vertical force is in contrast with the long period (approximately 150 sec) southward horizontal single force which was determined by a previous study and interpreted to be due to the massive landslide. Previously announced in STAR as N83-15968

Kanamori, H.↗

The structure and evolution of Jupiter - The fluid contraction stage

The complete evolution of a contracting star of Jovian mass consisting of a convective adiabatic homogeneous fluid is determined using stellar structure methods, improved model atmosphere calculations, and substantially improved thermodynamic properties for hydrogen and hydrogen-helium fluids. The model atmospheres are calculated in the form of time-averaged vertical temperature structures, including all relevant sources of opacity and a solar energy deposition component, and the thermodynamic properties are modified to obtain better agreement with Monte Carlo results for metallic fluids. The resultant gravitationally contracting evolutionary models are found to have two phases: an early stellar phase similar to a typical low-mass pre-main-sequence body and a later phase constituting an approach to a degenerate-dwarf cooling curve. The first phase is shown to have high luminosities and internal temperatures, while the second gives excellent agreement with the observed radius and luminosity of Jupiter. Analysis indicates that the equation of state and superadiabaticity have the strongest influence on evolution over planetary time scales.

Graboske, H. C., Jr.↗

Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning

Modern vehicles rely on a myriad of electronic control units (ECUs) interconnected via controller area networks (CANs) for critical operations. Despite their ubiquitous use and reliability, CANs are susceptible to sophisticated cyberattacks, particularly masquerade attacks, which inject false data that mimic legitimate messages at the expected frequency. These attacks pose severe risks such as unintended acceleration, brake deactivation, and rogue steering. Traditional intrusion detection systems (IDS) often struggle to detect these subtle intrusions due to their seamless integration into normal traffic. This paper introduces a novel framework for detecting masquerade attacks in the CAN bus using graph machine learning (ML). We hypothesize that the integration of shallow graph embeddings with time series features derived from CAN frames enhances the detection of masquerade attacks. We show that by representing CAN bus frames as message sequence graphs (MSGs) and enriching each node with contextual statistical attributes from time series, we can enhance detection capabilities across various attack patterns compared to using graph-based features only. Our method ensures a comprehensive and dynamic analysis of CAN frame interactions, improving robustness and efficiency. Extensive experiments on the ROAD dataset validate the effectiveness of our approach, demonstrating statistically significant improvements in the detection rates of masquerade attacks compared to a baseline that uses graph-based features only as confirmed by Mann-Whitney U and Kolmogorov-Smirnov tests (p < 0.05) .

Marfo, William [Univ. of Texas, El Paso, TX (Unite↗

Data for Intra- and inter-annual variability of nitrification in the rhizosphere of field-grown bioenergy sorghum

These data were collected in 2018 and 2019 at the University of Illinois Energy Farm (N 40.063607, W 88.206926). During each growing season, bulk and rhizosphere soil were collected from replicate Sorghum bicolor nitrogen use efficiency trial plots at three separate time points (approximately July 1, August 1, and September 1). We measured soil moisture, pH, soil nitrate and ammonium, potential nitrification, potential denitrification, and extracted and sequenced the V4 region of the 16S rRNA gene for microbial community analysis. All microbial sequence data is archived in the National Center for Biotechnology Information’s (NCBI) Sequence Read Archive (accession number SRP326979, project number PRJNA741261).

bioenergy↗

Scalability of high-performance PDE solvers

Performance tests and analyses are critical to effective high-performance computing software development and are central components in the design and implementation of computational algorithms for achieving faster simulations on existing and future computing architectures for large-scale application problems. In this article, we explore performance and space-time trade-offs for important compute-intensive kernels of large-scale numerical solvers for partial differential equations (PDEs) that govern a wide range of physical applications. We consider a sequence of PDE-motivated bake-off problems designed to establish best practices for efficient high-order simulations across a variety of codes and platforms. We measure peak performance (degrees of freedom per second) on a fixed number of nodes and identify effective code optimization strategies for each architecture. In addition to peak performance, we identify the minimum time to solution at 80% parallel efficiency. The performance analysis is based on spectral and p-type finite elements but is equally applicable to a broad spectrum of numerical PDE discretizations, including finite difference, finite volume, and h-type finite elements.

97 MATHEMATICS AND COMPUTING↗

Performance Analysis of Direct-Sequence Code-Division Multiple-Access Communications with Asymmetric Quadrature Phase-Shift-Keying Modulation

This article considers a quaternary direct-sequence code-division multiple-access (DS-CDMA) communication system with asymmetric quadrature phase-shift-keying (AQPSK) modulation for unequal error protection (UEP) capability. Both time synchronous and asynchronous cases are investigated. An expression for the probability distribution of the multiple-access interference is derived. The exact bit-error performance and the approximate performance using a Gaussian approximation and random signature sequences are evaluated by extending the techniques used for uniform quadrature phase-shift-keying (QPSK) and binary phase-shift-keying (BPSK) DS-CDMA systems. Finally, a general system model with unequal user power and the near-far problem is considered and analyzed. The results show that, for a system with UEP capability, the less protected data bits are more sensitive to the near-far effect that occurs in a multiple-access environment than are the more protected bits.

Wang, C.-W.↗

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗

Effect of fiber reinforcement on the process parameters of injection molding manufacturing process

Use of fillers with the resin is common in injection molding manufacturing technique to enhance the stiffness and strength of the manufactured components. However, the addition of fillers changes the rheological and mechanical properties of the material, required adjustments in the process parameters used for the manufacturing. The present study aims to investigate this impact of fillers on the process parameters of the injection molding manufacturing process. Neat Acrylonitrile Butadiene Styrene (ABS) and ABS reinforced with short glass fibers are used as the materials to perform the comprehensive numerical analysis including complete process sequence, namely filling, packing, cooling and warpage. Parametric studies are conducted to optimize the manufacturing process for minimal warpage (or shrinkage) in the produced part. The selected process parameters for the parametric study include cooling time, packing pressure, and mold temperature, all of which directly impact the quality of the manufactured parts. The optimal values obtained for these parameters are compared to examine the effect fiber reinforcement has on the manufacturing process.

Garg, Nikhil↗

Development of a three dimensional numerical water quality model for continental shelf applications

A model to predict the distribution of water quality parameters in three dimensions was developed. The mass transport equation was solved using a non-dimensional vertical axis and an alternating-direction-implicit finite difference technique. The reaction kinetics of the constituents were incorporated into a matrix method which permits computation of the interactions of multiple constituents. Methods for the computation of dispersion coefficients and coliform bacteria decay rates were determined. Numerical investigations of dispersive and dissipative effects showed that the three-dimensional model performs as predicted by analysis of simpler cases. The model was then applied to a two dimensional vertically averaged tidal dynamics model for the Providence River. It was also extended to a steady state application by replacing the time step with an iteration sequence. This modification was verified by comparison to analytical solutions and applied to a river confluence situation.

Spaulding, M.↗

A Coupled Nonlinear Spacecraft Attitude Controller and Observer with an Unknown Gyro Misalignment and Gyro Bias

A nonlinear control scheme for attitude control of a spacecraft is combined with a nonlinear gyro misalignment and bias observer for the case of constant gyro misalignment and bias. A persistency of excitation analysis shows the observer gyro bias estimates converge to the true bias values exponentially fast. The convergence of the misalignment estimates is also presented. Then; the resulting coupled, closed loop dynamics are proven by a Lyapunov analysis to be globally stable, with asymptotically perfect tracking. The analysis is extended to consider the effects of noise in addition to the gyro misalignment and bias. A simulation of the proposed observer-controller design is given for a rigid spacecraft tracking a specified, time-varying attitude sequence to illustrate the theoretical claims.

Thienel, Julie↗

Tracking Dendritic Growth in Hydrogen-Based Hematite Reduction via Computer Vision

The reduction of hematite to metallic iron using hydrogen (H2) as a reducing agent presents a promising pathway for decarbonizing steel production. In this study, we employ a combination of in situ confocal scanning laser microscopy (CSLM) and advanced computer vision techniques to quantitatively analyze dendritic growth of ferrite during H2-based reduction of iron oxide at high temperatures. A workflow integrating Watershed Image Segmentation (WIS) and Lucas-Kanade Optical Flow (LKOF) is developed to extract both global and local kinetic information from time-resolved micrograph sequences. H2 reduction experiments conducted at 1400 degrees C and 1500 degrees C demonstrate a clear correlation between temperature and reduction rate, as evidenced by accuracy of fitted Johnson-Mehl-Avrami-Kolmogorov (JMAK) parameters. Optical flow analysis further elucidates the anisotropic and branched nature of dendritic growth, providing spatially resolved velocity fields that correlate well with global transformation kinetics. The proposed methodology demonstrates strong agreement with experimental measurements and literature values, offering a robust framework for automated image-based analysis to study kinetics through microstructural evolution in the reduction of iron ore, and likely other reaction-diffusion phenomena.

08 HYDROGEN↗