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At least 1,369 records · Page 76

Identifying Key Environmental Factors Explaining Temporal Patterns of DOC Export From Watersheds in the Conterminous United States

The export of dissolved organic carbon (DOC) from a watershed is a key component of the terrestrial biosphere carbon cycle. There is a need to improve our understanding of how and by how much various environmental factors are driving the temporal patterns of DOC export in order to accurately model and evaluate terrestrial carbon storage and fluxes. In this synthesis, we compiled observational data sets from 14 watersheds in the conterminous United States spanning the time period from 1981 to 2017. We used these data sets to examine the relative impacts of various climate, atmospheric deposition, and land cover factors on the temporal patterns of DOC export across watersheds of different sizes and landscape conditions, as well as the time-series autocorrelation of DOC export. Overall, our results suggest that the dominant factor on an annual scale was the amount of precipitation, which had a positive correlation with DOC export from a watershed. Overall increasing nitrogen deposition was coincident with increasing DOC export, and increasing sulfur deposition was coincident with declining DOC export. The seasonal pattern of DOC export was strongly regulated by air temperature, the long-term trend was negatively influenced by increasing sulfur deposition, and no obvious autocorrelation was detected in DOC export. In addition, higher rates of DOC export were positively correlated with greater area of wetlands within a watershed, but was not found to be strongly related to any of the other land cover types.

54 ENVIRONMENTAL SCIENCES↗

Intermittent Criticality Multi‐Scale Processes Leading to Large Slip Events on Rough Laboratory Faults

Abstract We discuss data of three laboratory stick‐slip experiments on Westerly Granite samples performed at elevated confining pressure and constant displacement rate on rough fracture surfaces. The experiments produced complex slip patterns including fast and slow ruptures with large and small fault slips, as well as failure events on the fault surface producing acoustic emission bursts without externally‐detectable stress drop. Preparatory processes leading to large slips were tracked with an ensemble of ten seismo‐mechanical and statistical parameters characterizing local and global damage and stress evolution, localization and clustering processes, as well as event interactions. We decompose complex spatio‐temporal trends in the lab‐quake characteristics and identify persistent effects of evolving fault roughness and damage at different length scales, and local stress evolution approaching large events. The observed trends highlight labquake localization processes on different spatial and temporal scales. The preparatory process of large slip events includes smaller events marked by confined bursts of acoustic emission activity that collectively prepare the fault surface for a system‐wide failure by conditioning the large‐scale stress field. Our results are consistent overall with an evolving process of intermittent criticality leading to large failure events, and may contribute to improved forecasting of large natural earthquakes.

Geochemistry & Geophysics↗

Online Voltage Event Detection Using Synchrophasor Data with Structured Sparsity-Inducing Norms

This paper develops an accurate and computationally efficient data-driven framework to detect voltage events from PMU data streams. It develops an innovative Proximal Bilateral Random Projection (PBRP) algorithm to quickly decompose the PMU data matrix into a low-rank matrix, a row-sparse event-pattern matrix and a noise matrix. Here, the row-sparse pattern matrix significantly distinguishes events from normal behavior. These matrices are then fed into a clustering algorithm to separate voltage events from normal operating conditions. Large-scale numerical study results on real-world PMU data show that the proposed algorithm is computationally more efficient and achieves higher F scores than state-of-the-art benchmarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗

The use of artificial electron beams as probes of the distant magnetosphere

Experiments are reported in which electron beams were injected into the magnetosphere (with up to 40 kev energy and at current up to 0.8 A) to diagnose the plasma processes at great distance by measurements made in the ionosphere. In some of the experiments, the conjugate region atmosphere was used to detect the electron beam; in others, conjugate echoes were detected near the injection region. The echoes were found to respond to changes in the convection fields and to reflect auroral zone activity. Theoretical and experimental echo patterns are discussed. Evidence for beam pitch angle scattering and altered mirror heights is presented. The use of the atmospheric response to electron beams in the loss cone as a detector has been achieved using optical, X-ray, and radar techniques.

Winckler, J. R.↗

Resonance fluorescence calculations for some sulphur diatomics in comets

Statistical equilibrium calculations have been carried out for S2 which was detected in Comet IRAS-Araki-Alcock and for SO, SH and CS+ which are likely to be present in the cometary comas. In all cases, a pattern of features of similar intensity is predicted - so that identifications are possible even when signal : noise is poor and other emissions interfere. These results can guide searches and help confirm the presence of these features in cometary spectra.

Krishna Swamy, K. S.↗

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Key, J.↗

Measurement of subresolution terrain displacements using SPOT panchromatic imagery

It is shown that satellite-derived imagery can be used to measure subresolution horizontal terrain displacements associated with present-day earthquakes, sand dune migration, glacial motion, coastal sediment transport, and pre-eruptive volcanic processes. This use of these data allows the detection of change and the determination of rates of many environmental processes worldwide. The premise of the method is that areally extensive, subresolution spatial differences in ground patterns between images acquired at different times can be accurately measured to high precision and can be distinguished from systematic image differences, such as those due to sensing-system attitude variations. Thus far, a preliminary algorithm has been tested that shows that the approach is reasonable.

Crippen, Robert E.↗

Active and Passive Microwave Determination of the Circulation and Characteristics of Weddell and Ross Sea Ice

A combination of satellite microwave data sets are used in conjunction with ECMWF (Medium Range Weather Forecasts) and NCEP (National Center for Environment Prediction) meteorological analysis fields to investigate seasonal variability in the circulation and sea-ice dynamics of the Weddell and Ross Seas. Results of sea-ice tracking using SSM/I (Special Sensor Microwave Imager), Scatterometer and SAR images are combined with in-situ data derived from Argos buoys and GPS drifters to validate observed drift patterns. Seasonal 3-month climatologies of ice motion and drift speed variance illustrate the response of the sea-ice system to seasonal forcing. A melt-detection algorithm is used to track the onset of seasonal melt, and to determine the extent and duration of atmospherically-led surface melting during austral summer. Results show that wind-driven drift regulates the seasonal distribution and characteristics of sea-ice and the intensity of the cyclonic Gyre circulation in these two regions.

Drinkwater, Mark R.↗

Design of a Borescope for Extravehicular Non-Destructive Applications

Anomalies such as corrosion, structural damage, misalignment, cracking, stress fiactures, pitting, or wear can be detected and monitored by the aid of a borescope. A borescope requires a source of light for proper operation. Today s current lighting technology market consists of incandescent lamps, fluorescent lamps and other types of electric arc and electric discharge vapor lamp. Recent advances in LED technology have made LEDs viable for a number of applications, including vehicle stoplights, traffic lights, machine-vision-inspection, illumination, and street signs. LEDs promise significant reduction in power consumption compared to other sources of light. This project focused on comparing images taken by the Olympus IPLEX, using two different light sources. One of the sources is the 50-W internal metal halide lamp and the other is a 1 W LED placed at the tip of the insertion tube. Images acquired using these two light sources were quantitatively compared using their histogram, intensity profile along a line segment, and edge detection. Also, images were qualitatively compared using image registration and transformation [l]. The gray-level histogram, edge detection, image profile and image registration do not offer conclusive results. The LED light source, however, produces good images for visual inspection by an operator. Analysis using pattern recognition using Eigenfaces and Gaussian Pyramid in face recognition may be more useful.

Bachnak, Rafic↗

Southern Wyoming Ecological Forecasting: Monitoring Cheatgrass in Southern Wyoming and Northern Colorado to Inform Management Efforts Post-Mullen Fire

Cheatgrass (Bromus tectorum) is a prominent invasive species in the Intermountain West that has the potential to out-compete native plant species, reduce biodiversity, and reduce the quality of habitat for ungulates. Furthermore, because cheatgrass readily establishes in disturbed landscapes, it can potentially increase fuel loads and exacerbate wildfire risk. In 2020, the Mullen Fire burned 176,878 acres in Carbon and Albany Counties, Wyoming and Jackson County, Colorado. Large fires such as this one raise concern for partners at the United States Forest Service and the United States Geological Survey Fort Collins Science Center, who are tasked with rapidly detecting and controlling invasive species in the post-fire environment. We developed a Random Forest model trained by in-situ field data and spectral indices such as Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index derived from Landsat 8 Operational Land Imager, Sentinel-2 MultiSpectral Instrument, and Shuttle Radar Topography Mission to detect and map cheatgrass presence during the 2021 growing season. The team successfully created a spectral cheatgrass detection map in the study area (RMSE = 13.71, R2 = 0.34). We also produced a NDVI time-series derived from Sentinel-2 MSI to analyze vegetation recovery patterns.

Dahlia Shahin↗

Magnetically Charged Superdomain Walls In Square Artificial Spin Ice

We report direct evidence that magnetically charged superdomain walls form spontaneously in two dimensional square artificial spin ice nanostructures in response to external magnetic fields. These extended magnetic defects were revealed by the development of internal structure, which varies as a function of applied magnetic field, within the Bragg peaks of resonant soft x-ray magnetic scattering patterns. Magnetically charged superdomain walls extend over tens of lattice sites and do not necessarily align with the applied field. Our results illustrate a novel approach to detect hierarchical magnetic structures within spin textures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection

A significant portion of the literature on fault localization assumes (more or less explicitly) that there are sufficient reliable measurements to guarantee that the system is observable. While several heuristics exist to break the observability barrier, they mostly rely on recognizing spatio-temporal patterns, without giving insights on how the performance are tied with the system features and the sensor deployment. In this paper, we try to fill this gap and investigate the limitations and performance limits of fault localization using Phasor Measurement Units (PMUs), in the low measurements regime, i.e., when the system is unobservable with the measurements available. Our main contribution is to show how one can leverage the scarce measurements to localize different type of distribution line faults (three-phase, single-phase to ground,..) at the level of sub-graph, rather than with the resolution of a line. Here, we show that the resolution we obtain is strongly tied with the graph clustering notion in network science.

Community Detection↗

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland. AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring Cognitive States: Methods for Detecting Physiological Temporal Fingerprints

Cognitive state detection and its relationship to observable physiologically telemetry has been utilized for many human-machine and human-cybernetic applications. This paper aims at understanding and addressing if there are unique psychophysiological patterns over time, a ”physiological temporal fingerprint”, that is associated with specific cognitive states. This preliminary work involves commercial airline pilots completing experimental benchmark task inductions of three cognitive states: 1) Channelized Attention (CA); 2) High Workload (HW); and 3) Low Workload (LW). We approach this objective by modeling these "fingerprints" through the use of Hidden Markov Models and Entropy analysis to evaluate if the transitions over time are complex or rhythmic/predictable by nature. Our results indicate that cognitive states do have unique complexity of physiological sequences that are statistically different from other cognitive states. More specifically, CA has a significantly higher temporal psychophysiological complexity than HW and LW in EEG and ECG telemetry signals. With regards to respiration telemetry, CA has a lower temporal psychophysiological complexity than HW and LW. Through our preliminary work, addressing this unique underpinning can inform whether these underlying dynamics can be utilized to understand how humans transition between cognitive states and for improved detection of cognitive states.

Napoli, Nicholas J.↗

Comprehensive characterization of N- and O- glycosylation of SARS-CoV-2 human receptor angiotensin converting enzyme 2

The emergence of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created the need for development of new therapeutic strategies. Understanding the mode of viral attachment, entry and replication has become a key aspect of such interventions. The coronavirus surface features a trimeric spike (S) protein that is essential for viral attachment, entry and membrane fusion. The S protein of SARS-CoV-2 binds to human angiotensin converting enzyme 2 (hACE2) for entry. Herein, we describe glycomic and glycoproteomic analysis of hACE2 expressed in HEK293 cells. We observed high glycan occupancy (73.2 to 100%) at all seven possible N-glycosylation sites and surprisingly detected one novel O-glycosylation site. To deduce the detailed structure of glycan epitopes on hACE2 that may be involved in viral binding, we have characterized the terminal sialic acid linkages, the presence of bisecting GlcNAc and the pattern of N-glycan fucosylation. We have conducted extensive manual interpretation of each glycopeptide and glycan spectrum, in addition to using bioinformatics tools to validate the hACE2 glycosylation. Our elucidation of the site-specific glycosylation and its terminal orientations on the hACE2 receptor, along with the modeling of hACE2 glycosylation sites can aid in understanding the intriguing virus-receptor interactions and assist in the development of novel therapeutics to prevent viral entry. Here, the relevance of studying the role of ACE2 is further increased due to some recent reports about the varying ACE2 dependent complications with regard to age, sex, race and pre-existing conditions of COVID-19 patients.

59 BASIC BIOLOGICAL SCIENCES↗

Fuzzification of Electromagnetic Interference Patterns Onboard Commercial Airliners Due to Wireless Technology

The use of portable wireless technology has increased dramatically over the past few years. Over the years however, numerous reports have cited portable electronic devices (PEDs) as a possible cause of electromagnetic interference (EMI) to aircraft navigation and communication radio systems. PEDs may act as transmitters and their signals may be detected by the various radio receiver antennas installed on the aircraft. Measurement of the radiated field coupling between passenger cabin locations and aircraft communication and navigation receivers, via their antennas is defined herein as interference path loss (IPL). Personnel from NASA Langley Research Center, Eagles Wings Inc., and United Airlines performed extensive IPL measurements on several Boeing 737 airplanes. In previous work, the IPL data collected was graphically plotted and presented using MATLAB. This paper provides an introductory result of modeling EMI patterns using Fuzzy Logic, using the graphical analysis of the IPL data summarized. The application of fuzzy logic seeks to provide a means of estimating IPL at various locations within an airplane passenger cabin using simple modeling parameters. Fuzzy logic methods may provide a means to assess IPL characteristics of aircraft that have not been subject to expensive measurement or modeling processes and may also be useful for estimating the merit of aircraft design changes intended to minimize the potential for EMI.

Jafri, Madiha↗

Radiation damage in polymer films from grazing-incidence X-ray scattering measurements

Grazing-incidence X-ray scattering (GIXS) is widely used to analyze the crystallinity and nanoscale structure in thin polymer films. However, ionizing radiation will generate free radicals that initiate cross-linking and/or chain scission, and structural damage will impact the ordering kinetics, thermodynamics, and crystallinity in many polymers. We report a simple methodology to screen for beam damage that is based on lithographic principles: films are exposed to patterns of x-ray radiation, and changes in polymer structure are revealed by immersing the film in a solvent that dissolves the shortest chains. The experiments are implemented with high throughput using the standard beam line instrumentation and a typical GIXS configuration. The extent of damage (at a fixed radiation dose) depends on a range of intrinsic material properties and experimental variables, including the polymer chemistry and molecular weight, exposure environment, film thickness, and angle of incidence. The solubility switch for common polymers is detected within 10-60 sec at ambient temperature, and we verified that this first indication of damage corresponds with the onset of network formation in glassy polystyrene and a loss of crystallinity in polyalkylthiophenes. Therefore, grazing-incidence x-ray patterning offers an efficient approach to determine the appropriate data acquisition times for any GIXS experiment.

36 MATERIALS SCIENCE↗