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At least 1,747 records · Page 97

Real-time tracking of protein unfolding with time-resolved x-ray solution scattering

The correct folding of proteins is of paramount importance for their function, and protein misfolding is believed to be the primary cause of a wide range of diseases. Protein folding has been investigated with time-averaged methods and time-resolved spectroscopy, but observing the structural dynamics of the unfolding process in real-time is challenging. Here, we demonstrate an approach to directly reveal the structural changes in the unfolding reaction. We use nano- to millisecond time-resolved x-ray solution scattering to probe the unfolding of apomyoglobin. The unfolding reaction was triggered using a temperature jump, which was induced by a nanosecond laser pulse. We demonstrate a new strategy to interpret time-resolved x-ray solution scattering data, which evaluates ensembles of structures obtained from molecular dynamics simulations. We find that apomyoglobin passes three states when unfolding, which we characterize as native, molten globule, and unfolded. The molten globule dominates the population under the conditions investigated herein, whereas native and unfolded structures primarily contribute before the laser jump and 30 μs after it, respectively. The molten globule retains much of the native structure but shows a dynamic pattern of inter-residue contacts. Our study demonstrates a new strategy to directly observe structural changes over the cause of the unfolding reaction, providing time- and spatially resolved atomic details of the folding mechanism of globular proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Thunderstorm-environment interactions determined with three-dimensional trajectories

Diagnostically determined three dimensional trajectories were used to reveal some of the scale interaction processes that occur between convective storms and their environment. Data from NASA's fourth Atmospheric Variability Experiment are analyzed. Two intense squall lines and numerous reports of severe weather occurred during the period. Convective storm systems with good temporal and spatial continuity are shown to be related to the development and movement of short wave circulation systems aloft that propagate eastward within a zonal mid tropospheric wind pattern. These short wave systems are found to produce the potential instability and dynamic triggering needed for thunderstorm formation. The environmental flow patterns, relative to convective storm systems, are shown to produce large upward air parcel movements in excess of 50 mb/3h in the immediate vicinity of the storms. The air undergoing strong lifting originates as potentially unstable low level air traveling into the storm environment from southern and southwestern directions. The thermo and hydrodynamical processes that lead to changes in atmospheric structure before, during, and after convective storm formation are described using total time derivatives of pressure or net vertical displacement, potential temperature, and vector wind calculated by following air parcels.

Wilson, G. S.↗

Observational requirements for the regional scale

Observational requirements are provided for the 'regional scale' (10(exp 2) to 10(exp 3) km space scale; 3 to 24 h time scale). Given this range, the regional scale represents a spatial and temporal domain in which important scale-interactive processes occur that act to concentrate large vertical wind shears, significant horizontal thermal gradients, and vertical motion patterns into narrow regions. A short review of the mass and momentum adjustments associated with jet streak-induced circulations is discussed. Evidence for the need to specify the wind field in the upper troposphere to accurately simulate forcing for the transverse circulations is also presented. The importance of specifying temperature tendency to resolve the lower tropospheric portion of the transverse circulations is highlighted. The observational requirements are then discussed, along with possible approaches for meeting the requirements on the regional scale.

Uccellini, Louis W.↗

Spectroscopic measurements of element abundances in the solar corona: Variations on the FIP theme

Solar wind and solar energetic particle (SEP) data yield systematic differences between elemental abundances in the corona and in the photosphere related to the first ionization potential (FIP) of the elements: low-FIP elements are preferentially enhanced relative to high-FIP elements by about a factor of four. Spectroscopic studies of the inner corona show that such a pattern may apply on average but not in detail for coronal loops: substantial abundance differences occur between different types of coronal structures, and variations have been found from flare to flare, from one active region to another, and over time in the same region; further, in some flares, anomalies such as enhanced Ne:O ratios, distinctly at odds with the FIP pattern, show that a competing element selection mechanism sometimes operates. Details of the observed abundance variability -- such as the magnitude of the variations, the relevant temporal and spatial scales, and correlations with other properties of the given coronal structure -- may give important clues to the processes which supply and heat the corona, or they may reflect the changing physical conditions or locations where those processes take place. However, many such details remain to be established definitively. At present, abundance variability is primarily a major complication to data analysis and interpretation. However, once it is better understood, it may provide a new diagnostic tool for probing the lower layers of the solar atmosphere.

Saba, J. L. R.↗

Prediction of the Acoustic Field Associated with Instability Wave Source Model for a Compressible Jet

This paper provides preliminary results of the study of the acoustic radiation from the source model representing spatially-growing instability waves in a round jet at high speeds. The source model is briefly discussed first followed by the analysis of the produced acoustic directivity pattern. Two integral surface techniques are discussed and compared for prediction of the jet acoustic radiation field.

Golubev, Vladimir↗

Radar Cross Section of Orbital Debris Objects

This discussion is concerned with the radar-data analysis and usage involved in the building of model orbital debris (OD) populations in the near-Earth environment, focusing on radar cross section (RCS). While varying with radar wavelength, physical dimension, material composition, overall shape and structure, the RCS of an irregular object is also strongly dependent on its spatial orientation. The historical records of observed RCSs for cataloged OD objects in the Space Surveillance Network are usually distributed over an RCS range, forming respective characteristic patterns. The National Aeronautics and Space Administration (NASA) Size Estimation Model provides an empirical probability-density function of RCS as a function of “effective diameter” (or “characteristic length”), which makes it feasible to predict possible RCS distributions for a given model OD population and to link data with model from a statistical perspective. The discussion also includes application of the widely used method of moments (MoM) and the Generalized Multi-particle Mie-solution (GMM) in the prediction of the RCS of arbitrarily shaped objects. Theoretical calculation results for an aluminum cube are compared with corresponding experimental measurements.

Xu, Yu-Lin↗

Phytoplankton pigment patterns and wind forcing off central California

Mesoscale variability in phytoplankton pigment distributions of central California during the spring-summer upwelling season are studied via a 4-yr time series of high-resolution coastal zone color scanner imagery. Empirical orthogonal functions are used to decompose the time series of spatial images into its dominant modes of variability. The coupling between wind forcing of the upper ocean and phytoplankton distribution on mesoscales is investigated. Wind forcing, in particular the curl of the wind stress, was found to play an important role in the distribution of phytoplankton pigment in the California Current. The spring transition varies in timing and intensity from year to year but appears to be a recurrent feature associated with the rapid onset of the upwelling-favorable winds. Although the underlying dynamics may be dominated by processes other than forcing by wind stress curl, it appears that curl may force the variability of the filaments and hence the pigment patterns.

Abbott, Mark R.↗

Examining Perceptual Luminance Uniformity of Simulated Luminaire Patterns

Luminaire luminance uniformity is an important aspect that can affect perceived lighting quality, discomfort glare, and efficacy. While several metrics have been proposed to characterize luminance uniformity, previous studies have shown that current metrics such as Max:Min or Avg:Min luminance ratios can be insensitive to important differences in luminance gradient that may affect perceived uniformity. In an attempt to resolve this issue, previous studies incorporated a contrast sensitivity function for the human eye based on spatial frequency, such as in the UHVS metric; however, this metric has not been comprehensively studied in relation to perceived uniformity ratings. The study presented in this paper aimed to examine the relationship between the UHVS metric and perceived uniformity ratings. Specifically, the study used a web-based questionnaire that presented simulated luminance patterns and asked participants to assess uniformity using a two-alternative forced-choice procedure. Responses were collected and analyzed from 94 participants. The results showed a significant correlation and relationship between the UHVS metric and perceived uniformity. However, comparisons between patterns that had similar UHVS and between patterns that had larger differences in UHVS did not yield consistent results. These results suggest that the UHVS metric might be used for general guidance but may warrant further studies to better understand its sensitivity and improve its alignment with perceived uniformity ratings.

Abboushi, Belal K.↗

A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States

Abstract. Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time and observation-based GPP products. To address this critical gap, here we leverage a state-of-the-art vegetation index, near-infrared reflectance of vegetation (NIRV), along with accurate photosynthetically active radiation (PAR), to produce a SatelLite Only Photosynthesis Estimation (SLOPE) GPP product for the contiguous United States (CONUS). Compared to existing GPP products, the proposed SLOPE product is advanced in its spatial resolution (250 m versus >500 m), temporal resolution (daily versus 8 d), instantaneity (latency of 1 d versus >2 weeks) and quantitative uncertainty (on a per-pixel and daily basis versus no uncertainty information available). These characteristics are achieved because of several technical innovations employed in this study: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRV (SANIRV) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Cropland Data Layer (CDL) product to predict dynamic C4 crop fraction. Through developing a parsimonious model with only two slope parameters, the proposed SLOPE product explains 85 % of the spatial and temporal variations in GPP acquired from 49 AmeriFlux eddy-covariance sites (324 site years), with a root-mean-square error (RMSE) of 1.63 gC m−2 d−1. The median R2 over C3 and C4 crop sites reaches 0.87 and 0.94, respectively, indicating great potentials for monitoring crops, in particular bioenergy crops, at the field level. With such a satisfactory performance and its distinct characteristics in spatiotemporal resolution and instantaneity, the proposed SLOPE GPP product is promising for biological and environmental research, carbon cycle research, and a broad range of real-time applications at the regional scale. The archived dataset is available at https://doi.org/10.3334/ORNLDAAC/1786 (download page: https://daac.ornl.gov/daacdata/cms/SLOPE_GPP_CONUS/data/, last access: 20 January 2021) (Jiang and Guan, 2020), and the real-time dataset is available upon request.

54 ENVIRONMENTAL SCIENCES↗

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↗

Interpretation of Variations in Modis-Measured Greenness Levels of Amazon Forests During 2000 to 2009

This work investigates variations in satellite-measured greenness of Amazon forests using ten years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data. Corruption of optical remote sensing data with clouds and aerosols is prevalent in this region; filtering corrupted data causes spatial sampling constraints, as well as reducing the record length, which introduces large biases in estimates of greenness anomalies. The EVI data, analyzed in multiple ways and taking into account EVI accuracy, consistently show a pattern of negligible changes in the greenness levels of forests both in the area affected by drought in 2005 and outside it. Small random patches of anomalous greening and browning-especially prominent in 2009-appear in all ten years, irrespective of contemporaneous variations in precipitation, but with no persistence over time. The fact that over 90% of the EVI anomalies are insignificantly small-within the envelope of error (95% confidence interval) in EVI-warrants cautious interpretation of these results: there were no changes in the greenness of these forests, or if there were changes, the EVI data failed to capture these either because the constituent reflectances were saturated or the moderate resolution precluded viewing small-scale variations. This suggests a need for more accurate and spatially resolved synoptic views from satellite data and corroborating comprehensive ground sampling to understand the greenness dynamics of these forests.

MODIS↗

An efficient technique for determining apparent temperature distributions from antenna temperature measurements

A method by which the apparent microwave temperature characteristic of a flat scene is estimated from dual polarized measurements is derived and interpreted. Approximate linear relationships between antenna and apparent temperatures are established by weighting emission components in spherical bands under the assumption that the surface is isotropic. The weighting factors are formed by integrating the antenna pattern functions over these bands. The vector aspect of the formulation is retained to account for the difference between the definition of the antenna polarizations and the polarizations of the emitted fields. The method is largely applicable to the measurement of smooth temperature distributions by an antenna having good spatial resolution of the distributions and is considered efficient for inverting large volumes of measurements. Sample cases are presented and the implications of these cases on remote radiometer observations are discussed. It is shown that cross-coupling occurs between the polarizations of the emitted fields and the polarizations of the antenna. For this reason and because practical antennas have cross-polarized patterns associated with them, it is necessary to conduct measurements at both horizontal and vertical polarizations to realize the inversion. It is also made evident that thorough inversions require that the apparent temperatures be sampled at a sufficient number of points between nadir and zenith.

Claassen, J. P.↗

Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

Ecosystem structure and function are strongly impacted by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the Advanced Very High Resolution Radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982-2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987-1989, 1995-1997, and 1999. Sub- continental regions of Alaska and Central Canada had the highest proportion (greater than 90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

Potter, Christopher↗

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗

Near, far, wherever you are: simulations on the dose efficiency of holographic and ptychographic coherent imaging

Different studies in X-ray microscopy have arrived at conflicting conclusions about the dose efficiency of imaging modes involving the recording of intensity distributions in the near (Fresnel regime) or far (Fraunhofer regime) field downstream of a specimen. A numerical study is presented on the dose efficiency of near-field holography, near-field ptychography and far-field ptychography, where ptychography involves multiple overlapping finite-sized illumination positions. Unlike what has been reported for coherent diffraction imaging, which involves recording a single far-field diffraction pattern, it is found that all three methods offer similar image quality when using the same fluence on the specimen, with far-field ptychography offering slightly better spatial resolution and a lower mean error. These results support the concept that (if the experiment and image reconstruction are done properly) the sample can be near or far; wherever you are, photon fluence on the specimen sets one limit to spatial resolution.

42 ENGINEERING↗

Using Community Science to Reveal the Global Chemogeography of River Metabolomes

River corridor metabolomes reflect organic matter (OM) processing that drives aquatic biogeochemical cycles. Recent work highlights the power of ultrahigh-resolution mass spectrometry for understanding metabolome composition and river corridor metabolism. However, there have been no studies on the global chemogeography of surface water and sediment metabolomes using ultrahigh-resolution techniques. Here, we describe a community science effort from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to characterize global metabolomes in surface water and sediment that span multiple stream orders and biomes. We describe the distribution of key aspects of metabolomes including elemental groups, chemical classes, indices, and inferred biochemical transformations. We show that metabolomes significantly differ across surface water and sediment and that surface water metabolomes are more rich and variable. We also use inferred biochemical transformations to identify core metabolic processes shared among surface water and sediment. Finally, we observe significant spatial variation in sediment metabolites between rivers in the eastern and western portions of the contiguous United States. Our work not only provides a basis for understanding global patterns in river corridor biogeochemical cycles but also demonstrates that community science endeavors can enable global research projects that are unfeasible with traditional research models.

54 ENVIRONMENTAL SCIENCES↗

Wireless Patch Antenna Characterization for Live Health Monitoring Using Machine Learning

Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the sensor was performed using a Vector Network Analyzer (VNA) and a pair of interrogation antennas to capture resonance behavior under varying thermal and spatial conditions with sensitivities ranging from 0.052 to 0.20 $\frac{𝑀𝐻𝑧}{°C}$. Sensor calibration was conducted using a Long Short-Term Memory (LSTM) model, which leveraged temporal patterns to account for hysteresis effects. The calibration method demonstrated improved performance when combined with an LSTM model, achieving up to a 76% improvement in temperature estimation error when compared with Linear Regression (LR). The experiments highlighted an innovative solution for patch antenna-based non-contact temperature measurement, which addresses limitations with conventional methods such as RFID-based systems, infrared, and thermocouples.

20 FOSSIL-FUELED POWER PLANTS↗

Floor-fractured lunar craters

Observational data concerning floor-fractured craters on the lunar near and far sides are examined, including the morphologic classification of the craters, their spatial and size distributions, and their floor, peak, and rim elevations relative to the maria. Six morphologic classes and two subclasses are delineated on the basis of fracture pattern, crater floor depth, and floor type. These data are used to reconstruct a history of crater modification which accounts for the large differences in affected crater size and age, the small peak-rim elevation differences, remnant central peaks within mare-flooded craters and ringed plains, ridged and flat-topped rim profiles of heavily modified craters and ringed plains, as well as the absence of positive gravity anomalies in most floor-fractured craters and some large mare-filled craters. The results indicate that: (1) impact craters became centers of intrusions and volcanism generally related to periods of basin inundation by mare basalts; (2) some light-plains units in the highlands may be due to both impact ejecta and extrusions of light-colored lava or ash; (3) floor-fractured craters may have become important volcanic vents that contributed to the inundation of the lunar surface by mare basalts; and (4) the lunar highlands probably did not fully escape the epochs of mare flooding.

Schultz, P. H.↗