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At least 1,765 records · Page 98

Hydrogeological investigations in the Pampa of Argentina

In large areas of the Argentinian Pampa the salinization of ground water creates water supply difficulties. Investigations of satellite imagery (Landsat-1 and Skylab) which were based on an extensive ground survey revealed that differences in the vegetation cover are closely related to depth and salinity of ground water. Narrow elongated depressions called bajos are often the only indication of fresh ground water. They can be easily detected on the imagery. Due to their high resolution, Skylab photos even allow a quantitative estimation of fresh ground water situated below the bajos. In general however Landsat-1 imagery sufficed for evaluation. In the area of the Rio Tercero a fossil drainage pattern was discovered and in Corrientes province, soil types could be discriminated and compared to the Soil Map of the World.

Kruck, W.↗

Determination of particle size using measurement of scatter

A literature search was conducted to determine the state of the art particle size measurement by the light scatter technique. This technique may involve diffraction pattern analysis, location of minima and maxima in angular dependence of scattered light, magnitude of intensity verses angle, forward lobe scattered intensity ratio using two small angles, forward scatter in a small cone, and total scatter. Some of the more modern recordings and detection systems are video, holographic, and systems using optical processing.

Scott, R. L., Jr.↗

Improvement of vertical velocity measurements, part 3.4B

Vertical velocities are assumed to be measurable with vertically pointing antenna beams. An exact horizontal levelling and good phase calibration of the radar antenna system can yield real main-beam directions which do not significantly differ from calculated patterns. It is, thus, anticipated that antenna beams can be pointed exactly vertically. Because of area size and near-field limitations, VHF radar antennas have typically beam widths of more than several degrees. It is known that most of the reflectivity structures detected by vertically beaming VHF radars in the troposphere, stratosphere and lower mesosphere are aspect-sensitive. It cannot a priori be assumed that these structures are exactly horizontal. A few examples are investigated to support this statement.

Rottger, J.↗

Trace element analyses of spheres from the melt zone of the Greenland ice cap using synchrotron X ray fluorescence

Synchrotron X-ray fluorescence spectra of unpolished iron and chondritic spheres extracted from sediments collected on the melt zone of the Greenland ice cap allow the analysis of Ni, Cu, Zn, Ga, Ge, Pb, and Se with minimum detection limits on the order of several parts per million. All detected elements are depleted relative to chondritic abundance with the exception of Pb, which shows enrichments up to a factor of 500. An apparent anticorrelation between the Ni-content and trace element concentration was observed in both types of spherules. The fractionation patterns of the iron and chondritic spheres are not complementary and consequently the two iron spheres examined in this study are unlikely to result from ejection of globules of Fe/Ni from parent chondritic micrometeoroids.

Chevallier, P.↗

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Gupta, U. K.↗

Cusp and LLBL as Sources of the Isolated Dayside Auroral Feature During Northward IMF

An intense dayside proton aurora was observed by Imager for Magnetopause-to- Aurora Global Exploration Far Ultra-Violet imager (IMAGE FUV) for an extensive period of northward interplanetary magnetic field (IMF) on 17 and 18 September 2000. This aurora partially coincided with the auroral oval and intruded farther poleward into the polar cap, and it showed longitudinal motions in response to IMF By variation. Intense magnetosheath-like electron and ion precipitations have been simultaneously detected by Defense Meteorological Satellite Program (DMSP) above the poleward portion of the high-latitude dayside aurora. They resemble the typical plasmas observed in the low-altitude cusp. However, less intense electrons and more energetic ions were detected over the equatonvard part of the aurora. These plasmas are closer to the low-latitude boundary layer (LLBL) plasmas. Under strongly northward IMF, global ionospheric convection derived from Super Dual Auroral Radar Network (SuperDARN) radar measurements showed a four-cell pattern with sunward convection in the middle of the dayside polar cap and the dayside aurora corresponded to two different convection cells. This result further supports two source regions for the aurora. The cusp proton aurora is on open magnetic field lines convecting sunward whereas the LLBL proton aurora is on closed field lines convecting antisunward. These IMAGE, DMSP, and SuperDARN observations reveal the structure and dynamics of the aurora and provide strong evidence for magnetic merging occurring at the high-latitude magnetopause poleward from the cusp. This merging process was very likely quasi-stationary.

Chang, S.-W.↗

Functional Testing and Evaluation of Actiwatch Spectrum Devices for Launch on STS-133/ULF5

The Actiwatch Spectrum (AWS) is a wrist-worn device that may be used for obtaining ground or on-orbit light exposure patterns and movement data. The objective of this project was to prepare AWS devices for launch on STS-133/ULF5 by a means of implementing functional tests and engineering evaluations. The data obtained from these tests and evaluations served as a means for detecting any plausible issues that the AWS may encounter while on-orbit. Subsequent steps after detecting anomalies with AWS devices encompassed identifying their root causes and taking the steps needed to mitigate them. As a result of this study, the overall success of sleep/wake research studies for STS-133/ULF5 and future missions will be enhanced.

Rollins, Selisa F.↗

A spatially regularized detector for emergent/re-emergent disease outbreaks

Early detection of outbreaks caused by emergent pathogens, using epidemiological surveillance data i.e., daily case counts, is difficult. This is because the data tend to be noisy during the early epoch of the outbreak. In contrast, the spread-rate of the disease tends to be well-behaved, as it depends only on the mixing patterns of the population and the characteristics of the pathogen, neither of which behave erratically in space-time. In this report, we explore whether the spread-rate can be used for epidemiological surveillance, conditional on case count data. Estimating the spread-rate from case count data allows us to exploit exogenous information, e.g., incubation period distributions etc., which can considerably smooth out any erratic temporal behavior. Further, epidemiological dynamics are spatially correlated, and if case counts are available for multiple areal units e.g., counties, these correlations could potentially be used to suppress noise in the early epoch data. These exogenous information and structure are not exploited by conventional syndromic surveillance detectors to extract a well-behaved latent variable for monitoring purposes. The technical challenge lies in the estimation of the spread-rate field jointly over a collection of areal units; further, the spread-rate varies over time. We develop a method based on mean-field variational inference to approximately estimate the spread-rate field, using a Gaussian Random Field Model for spatial regularization. The method is tested on the estimation of spread-rate in the thirty-three counties of New Mexico and detect the arrival of the Fall 2020 COVID-19 wave in September 2020. We find that the method is scalable, but underestimates the uncertainty in the estimated spread-rate field. We detect the arrival of the Fall 2020 wave a week ahead of conventional syndromic surveillance algorithms, but our simplistic detection algorithm, based on simple anomaly detection, suffers from a high false positive rate, similar to conventional detectors.

59 BASIC BIOLOGICAL SCIENCES↗

Variational AutoEncoders Reveal Intensifying GPP Extremes in Continental United States based on CESM2 Simulations

Climate extremes significantly impact terrestrial carbon cycle dynamics, necessitating robust methods for detecting and analyzing anomalous behavior in plant productivity. This study presents a novel application of variational autoencoders (VAE) for identifying extreme events in gross primary productivity (GPP) from Community Earth System Model version 2 simulations across four AR6 regions in the Continental United States. We compare VAE-based anomaly detection with traditional singular spectral analysis (SSA) methods across three time periods: 1850-80, 1950-80, and 2050-80 under SSP5-8.5 scenario. The VAE architecture employs three dense layers and a latent space with input sequence length of 12 months, training on normalized GPP time series to reconstruct the GPP and identify anomalies based on reconstruction errors. Extreme events are defined using 5th percentile thresholds applied to both VAE and SSA anomalies. Results demonstrate strong regional agreement between VAE and SSA methods in spatial patterns of extreme event frequencies, despite VAE consistently producing higher threshold values (179-756 GgC for VAE vs. 100-784 GgC for SSA across regions and periods). Both methods reveal increasing magnitudes and frequencies of negative carbon cycle extremes toward 2050-80, particularly in Western and Central North America. The VAE approach shows comparable performance to established SSA techniques while offering computational advantages and enhanced capability for capturing non-linear temporal dependencies in carbon cycle variability. This research demonstrates the potential of deep learning approaches for extremes detection and provides a foundation for improved understanding of future carbon cycle risks under future conditions.

Sharma, Bharat [ORNL] (ORCID:0000000266982487)↗

Drifting oscillations in axion monodromy

In this paper, we study the pattern of oscillations in the primordial power spectrum in axion monodromy inflation, accounting for drifts in the oscillation period that can be important for comparing to cosmological data. In these models the potential energy has a monomial form over a super-Planckian field range, with superimposed modulations whose size is model-dependent. The amplitude and frequency of the modulations are set by the expectation values of moduli fields. We show that during the course of inflation, the diminishing energy density can induce slow adjustments of the moduli, changing the modulations. We provide templates capturing the effects of drifting moduli, as well as drifts arising in effective field theory models based on softly broken discrete shift symmetries, and we estimate the precision required to detect a drifting period. A non-drifting template suffices over a wide range of parameters, but for the highest frequencies of interest, or for sufficiently strong drift, it is necessary to include parameters characterizing the change in frequency over the e-folds visible in the CMB. Finally, we use these templates to perform a preliminary search for drifting oscillations in a part of the parameter space in the Planck nominal mission data.

79 ASTRONOMY AND ASTROPHYSICS↗

Energy resolution and efficiency of phonon-mediated kinetic inductance detectors for light detection

The development of sensitive cryogenic light detectors is of primary interest for bolometric experiments searching for rare events like dark matter interactions or neutrino-less double beta decay. Thanks to their good energy resolution and the natural multiplexed read-out, Kinetic Inductance Detectors (KIDs) are particularly suitable for this purpose. To efficiently couple KIDs-based light detectors to the large crystals used by the most advanced bolometric detectors, active surfaces of several cm{sup 2} are needed. For this reason, we are developing phonon-mediated detectors. In this paper, we present the results obtained with a prototype consisting of four 40 nm thick aluminum resonators patterned on a 2 × 2 cm{sup 2} silicon chip, and calibrated with optical pulses and X-rays. The detector features a noise resolution σ{sub E} = 154 ± 7 eV and an (18 ± 2)% efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evidence for a single-layer van der Waals multiferroic

Here we searched for signatures of type-II multiferroic order in ultrathin van der Waals materials, to determine if such a state, comprising coexisting electrical polarization and spin order with strong magnetoelectric effects, could persist down to a single-atomic layer. We reported the first observation of such a state in triangular lattice material NiI 2 . This system has a layered structure and built-in magnetic frustration that promotes a complex magnetic ground state with proper-screw spin helices. The spin helix pattern breaks inversion symmetry and induces electrical polarization via magnetoelectric coupling. We use circular dichroic Raman measurements to directly probe the magneto-chiral ground state and its electromagnon modes originating from dynamic magnetoelectric coupling. Using birefringence and second-harmonic generation measurements, we detect a highly anisotropic electronic state simultaneously breaking three-fold rotational and inversion symmetry. The evolution of the optical signatures as a function of temperature and layer number surprisingly revealed a multiferroic state that persists down to the ultrathin limit of monolayer NiI 2 . These observations establish NiI 2 and transition metal dihalides as a new platform for studying emergent multiferroic phenomena, chiral magnetic textures and ferroelectricity in the 2D limit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Patchy nuclear chain reactions

Stochastic fluctuations of the neutron population within a nuclear reactor are typically prevented by operating the core at a sufficient power, since a deterministic (i.e., exactly predictable) behavior of the neutron population is required by automatic safety systems to detect unwanted power excursions. In order to characterize the reactor operating conditions at which the fluctuations vanish, an experiment was designed and took place in 2017 at the Rensselaer Polytechnic Institute Reactor Critical Facility. This experiment however revealed persisting fluctuations and striking patchy spatial patterns in neutron spatial distributions. Here we report these experimental findings, interpret them by a stochastic modeling based on branching random walks, and extend them using a “numerical twin” of the reactor core. Consequences on nuclear safety will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Detecting rare neutral atomic-carbon absorbers with a deep neural network

ABSTRACT C i absorbers play an important role as indicators for exploring the presence of cold gas in the interstellar medium of galaxies. However, the current data base of C i absorbers is very limited due to their weak absorption feature and rarity. Here, we report results from a search of C i λλ1560, 1656 absorption lines using Mg ii absorbers as signposts with modified deep learning algorithms, which provides a very quick way to search for weak C i absorber candidates. A total of 107 C i absorbers were detected, which nearly doubles the size of previously known samples. In addition, we found 17 C i absorbers to be associated with 2175 Å dust absorbers (2DAs), i.e. about 16 per cent C i absorbers are associated with 2DAs. Comparing the average dust depletion patterns of C i absorbers with those of damped Lyman α absorbers (DLAs), Mg ii absorbers, Ca ii absorbers, and 2175 Å dust absorbers (2DAs) shows that C i absorbers generally have environments with more dust than DLAs, Mg ii, and Ca ii absorbers, but similar to dust in 2DAs. Similarity between the dust depletion pattern of C i absorbers to that of the warm disc in the Milky Way indicates that C i absorption clouds are possibly associated with disc components in distant galaxies. Therefore, C i absorbers are confirmed to be excellent probes to trace cold gas and dust in the Universe.

Ge, Jian↗

Feasibility of a feedback control of atomic self-organization in an optical cavity

Many interesting nonlinear effects are based on the strong interaction of motional degrees of freedom of atoms with an optical cavity field. Among them is the spatial self-organization of atoms in a pattern where the atoms group in either odd or even sites of the cavity-induced optical potential. An experimental observation of this effect can be simplified by using, along with the original cavity-induced feedback, an additional electronic feedback based on the detection of light leaking the cavity and the control of the optical potential for the atoms. Following our previous study, we show that this approach is more efficient from the laser power perspective than the original scheme without the electronic feedback.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantifying High-Performance Material Microstructure Using Nanomechanical Tools with Visual and Frequency Analysis

High-performance materials like ballistic fibers have remarkable mechanical properties owing to specific patterns of organization ranging from the molecular scale, to the micro scale and macro scale. Understanding these strategies for material organization is critical to improving the mechanical properties of these high-performance materials. In this work, atomic force microscopy (AFM) was used to detect changes in material composition at an extremely high resolution with transverse-stiffness scanning. New methods for direct quantification of material morphology were developed, and applied as an example to these AFM scans, although these methods can be applied to any spatially-resolved scans. These techniques were used to delineate between subtle morphological differences in commercial ultra-high-molecular-weight polyethylene (UHMWPE) fibers that have different processing conditions and mechanical properties as well as quantify morphology in commercial Kevlar®, a high-performance material with an entirely different organization strategy. Both frequency analysis and visual processing methods were used to systematically quantify the microstructure of the fiber samples in this study. These techniques are the first step in establishing structure-property relationships that can be used to inform synthesis and processing techniques to achieve desired morphologies, and thus superior mechanical performance.

Sandoz-Rosado, Emil↗

Sentinel

Network intrusion detection systems (NIDS) are commonplace in network security but they frequently employ algorithms that are computational demanding requiring hardware and software with significant power requirements. Two examples of such resource-intensive algorithms used for network security are regular expression matching and broader signature pattern matching which are commonly used in deep packet inspection (DPI). Network security algorithms that have large power requirements may be a challenge for low-power internet-of-things (IoT) environments, which generally lack the power resources to implement complex security measures like computationally expensive DPI at the edge. Furthermore, IoT environments incorporating 5G standalone networks have network latency constraints beyond just power that make DPI at the edge even more difficult. Programmable logic is ideally suited for machine learning inference for DPI because of its deep instruction level parallelism and single-cycle memory access. Machine learning approaches for DPI have been explored before using the programmable logic of field programmable gate arrays (FPGA) as a potential solution for NIDS approaches that would be power-suitable for IoT. However, those previous programmable logic NIDS approaches utilize either a supervised or unsupervised learning model. Sentinel utilizes the ensemble of these two machine learning approaches known as a semi-supervised approach which has shown promise in NIDS implementations. Sentinel provides a programmable logic implementation of a semi-supervised approach for DPI which operates at much lower power and latency than a GPU implementation with negligible loss of accuracy due to quantization through a logistic regressor.

Anderson, MatthewW [Idaho National Laboratory (INL↗

Final Technical Report for DE-SC0008149

The major goal of this project is to study spin waves in magnetic thin films, especially how spin waves respond to external stimuli. This is expected to lead to new insight into dynamic processes and new ideas for methods to control spin waves. Experimental studies are being done primarily using time- and spatially-resolved Brillouin light scattering (BLS) measurements on extended and patterned magnetic thin films. BLS is a versatile tool that provides a non-invasive probe of spin dynamics with frequencies of ~1 GHz to well over 100 GHz, diffraction-limited spatial resolution, 250-ps temporal resolution, and it is sensitive enough to detect thermal magnons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗