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SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) is a 10-channel infrared radiometer that is one of four instruments on the NASA TIMED (Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics) satellite mission to study the structure, energetics, chemistry, and dynamics of the Earth’s mesosphere and lower thermosphere. The TIMED spacecraft was launched into a 625 km circular polar orbit (74.1º inclination) via a Boeing Delta II rocket from Vandenberg Air Force Base on 7 December 2001. SABER continues to operate nominally and collect data routinely as it has for over 21 years. Over 2,200 peer-reviewed journal articles have been published worldwide using SABER data. A list of these articles is included in the Supporting Information accompanying this paper. This paper presents a detailed technical description of the SABER instrument including major subsystems of the instrument and technical performance parameters. This paper comprehensively describes the instrument and its components and provides final instrument design and performance parameters. The motivation for this paper is to document this information permanently for future reference. The Space Dynamics Laboratory (SDL) of Utah State University designed, fabricated, and calibrated the SABER instrument in close collaboration with NASA Langley Research Center, Hampton University, and Global Atmospheric Technologies and Science (GATS).

Enzyme reactivity is often enhanced by changes in oxidation state, spin state, and metal-ligand covalency of associated metallocofactors. The development of spectroscopic methods for studying these processes coincidentally with structural rearrangements is essential for elucidating metalloenzyme mechanisms. Herein, we demonstrate the feasibility of collecting X-ray emission spectra of metalloenzyme crystals at a 3rd generation synchrotron source. In particular, we report the development of a von Hamos spectrometer for the collection of Fe Kβ emission optimized for analysis of dilute biological samples. We further showcase its application in crystals of the immunosuppressive heme-dependent enzyme indoleamine 2,3-dioxygenase. Spectra from protein crystals in different states were compared with relevant reference compounds. Complementary density functional calculations assessing covalency support our spectroscopic analysis and identify active site conformations that correlate to high- and low-spin states. These experiments validate the suitability of an X-ray emission approach for determining spin states of previously uncharacterized metalloenzyme reaction intermediates.

In this work we study the effect of engineered disorder on the local magnetic response of proximity coupled superconducting island arrays by comparing scanning Superconducting Quantum Interference Device (SQUID) susceptibility measurements to a model in which we treat the system as a network of one-dimensional (1D) superconductor-normal metal-superconductor (SNS) Josephson junctions, each with a Josephson coupling energy $E_J$ determined by the junction length or distance between islands. We find that the disordered arrays exhibit a spatially inhomogeneous diamagnetic response which, for low local applied magnetic fields, is well described by this junction network model, and we discuss these results as they relate to inhomogeneous two-dimensional (2D) superconductors. Our model of the static magnetic response of the arrays does not fully capture the onset of nonlinearity and dissipation with increasing applied field, as these effects are associated with vortex motion due to the dynamic nature of the scanning SQUID susceptometry measurement. This work demonstrates a model 2D superconducting system with engineered disorder and highlights the impact of dissipation on the local magnetic properties of 2D superconductors and Josephson junction arrays., Main text: 9 pages, 5 figures. Supplementary material: 11 pages, 12 figures. Accepted to Phys. Rev. B. The first two authors contributed equally

Restoration planning requires a reliable seed supply, yet many projects occur in response to unplanned events. Identifying regions of greater risk could help guide seed procurement. Using fire perimeters (2000–2019), we investigated differences in fire occurrence (frequency, area burned, percent of area burned) among seed transfer zones within Cold Deserts of the US. We considered both provisional seed transfer zones (PSTZs), created using climate and stratified by ecoregion, and empirical seed transfer zones (ESTZs) for two species commonly used in restoration. Finally, we present a case study on fire occurrence within Northern Basin and Range greater sage-grouse Priority Areas for Conservation (PACs). Historic fire was effective for prioritizing seed zones: 23 of 132 PSTZs burned every year, and, within each ecoregion, two PSTZs comprised ≧ 50% of the total area burned across all years. Similarly, fire disproportionately occurred in some ESTZs; in the Northern Basin and Range, one (Artemisia tridentata - 83%) or two zones (Pseudoroegneria spicata - 65%) made up a majority of total area burned. Fire occurrence within PACs largely reflected the PSTZ and ESTZ priorities found for the ecoregion, with small exceptions. Imperiled PSTZs (high proportion burned) in PACs largely reflected the patterns found across the ecoregion, while imperiled ESTZs departed from ecoregional patterns. Considering historic disturbance can focus seed procurement efforts on regions that encounter regular disturbance, experience large disturbances, or have particular conservation value. This information can guide seed production, purchase, and storage, create more certainty for growers and managers, and ultimately increase restoration success.IMPLICATIONS FOR PRACTICEAvailable data on past disturbance patterns may inform strategies for prioritizing seed procurement decisions, especially as geospatial information becomes more widely availableThe methods presented here illustrate an approach for using historic disturbance data to identify regions that are of greatest need for seed collection and conservation, using seed transfer zones within US Cold Desert ecoregions as an exampleIdentifying regions that experience disturbance over large areas or are likely to be imperiled due to disturbance at a high proportion can guide the collection and conservation of plant materials and better align available plant material with future restoration needs

The California Current System is thought to be particularly vulnerable to ocean acidification, yet pH remains chronically undersampled along this coast, limiting our ability to assess the impacts of ocean acidification. To address this observational gap, we integrated the Deep-Sea-DuraFET, a solid-state pH sensor, onto a Spray underwater glider. Over the course of a year starting in April 2019, we conducted seven missions in central California that spanned 161 glider days and >1600 dives to a maximum depth of 1000 m. The sensor accuracy was estimated to be ± 0.01 based on comparisons to discrete samples taken alongside the glider (n = 105), and the precision was ±0.0016. CO2 partial pressure, dissolved inorganic carbon, and aragonite saturation state could be estimated from the pH data with uncertainty better than ± 2.5%, ± 8 μmol kg−1, and ± 2%, respectively. The sensor was stable to ±0.01 for the first 9 months but exhibited a drift of 0.015 during the last mission. The drift was correctable using a piecewise linear regression based on a reference pH field at 450 m estimated from published global empirical algorithms. These algorithms require accurate O2 as inputs; thus, protocols for a simple predeployment air calibration that achieved accuracy of better than 1% were implemented. The glider observations revealed upwelling of undersaturated waters with respect to aragonite to within 5 m below the surface near Monterey Bay. These observations highlight the importance of persistent observations through autonomous platforms in highly dynamic coastal environments.

The COVID-19 public health emergency caused widespread economic shutdown and unemployment. The resulting surge in Unemployment Insurance claims threatened to overwhelm the legacy systems state workforce agencies rely on to collect, process, and pay claims. In Rhode Island, we developed a scalable cloud solution to collect Pandemic Unemployment Assistance claims as part of a new program created under the Coronavirus Aid, Relief and Economic Security Act to extend unemployment benefits to independent contractors and gig-economy workers not covered by traditional Unemployment Insurance. Our new system was developed, tested, and deployed within 10 days following the passage of the Coronavirus Aid, Relief and Economic Security Act, making Rhode Island the first state in the nation to collect, validate, and pay Pandemic Unemployment Assistance claims. A cloud-enhanced interactive voice response system was deployed a week later to handle the corresponding surge in weekly certifications for continuing unemployment benefits. Cloud solutions can augment legacy systems by offloading processes that are more efficiently handled in modern scalable systems, reserving the limited resources of legacy systems for what they were originally designed. This agile use of combined technologies allowed Rhode Island to deliver timely Pandemic Unemployment Assistance benefits with an estimated cost savings of $502,000 (representing a 411% return on investment).

Lewis flax (Linum lewisii) is widely distributed across western North America and is currently used in native ecosystem restoration. There is also growing interest in de novo domestication of Lewis flax as a perennial oilseed crop. To better understand this species and facilitate both restoration and domestication, we used common gardens to assess biogeographical variation in a variety of seed and growth traits from 37 flax accessions, consisting of 35 wild populations from the Intermountain West region, the pre-variety germplasm Maple Grove (L. lewisii) and the cultivar ‘Appar’ (L. perenne) and related this variation to collection site geography and climate. Results from linear mixed models suggest there is extensive phenotypic variation among populations of Lewis flax within the Intermountain West. Using a multivariate approach, we identify a key suite of traits that are related to latitude and climate and may facilitate adaptation, including flowering indeterminacy, seed mass and stem number. These traits should be taken into account when considering the release of new germplasm for restoration efforts. We also find that Lewis flax seed contains desirably high amounts of alpha-linolenic acid and is otherwise mostly indistinguishable in fatty acid composition from oil-type varieties of domesticated flax (L. usitatissimum), making it a strong candidate for domestication. This study provides fundamental knowledge for future research into the ecology and evolution of Lewis flax, which will inform its use in both restoration and agriculture.

We survey the phase diagram of high-pressure molecular hydrogen with path integral molecular dynamics using a machine-learned interatomic potential trained with Quantum Monte Carlo forces and energies. Besides the HCP and C2/c-24 phases, we find two new stable phases both with molecular centers in the Fmmm-4 structure, separated by a molecular orientation transition with temperature. The high temperature isotropic Fmmm-4 phase has a reentrant melting line with a maximum at higher temperature (1450K at 150GPa) than previously estimated and crosses the liquid-liquid transition line around 1200K and 200GPa., Comment: 4 pages, 4 figures, updated acknowledgment

[EN] Exotic annual grasses invasion across northern Great Basin rangelands has promoted a grass-fire cycle that threatens the sagebrush (Artemisia spp.) steppe ecosystem. In this sense, high accumulation rates and persistence of litter from annual species largely increase the amount and continuity of fine fuels. Here, we highlight the potential use and transferability of remote sensing-derived products to estimate litter biomass on sagebrush rangelands in southeastern Oregon, and link fire regime attributes (fire-free period) with litter biomass spatial patterns at the landscape scale. Every June, from 2018 to 2021, we measured litter biomass in 24 field plots (60 m × 60 m). Two remote sensing-derived datasets were used to predict litter biomass measured in the field plots. The first dataset used was the 30-m annual net primary production (NPP) product partitioned into plant functional traits (annual grass, perennial grass, shrub, and tree) from the Rangeland Analysis Platform (RAP). The second dataset included topographic variables (heat load index -HLI- and site exposure index -SEI-) computed from the USGS 30-m National Elevation Dataset. Through a frequentist model averaging approach (FMA), we determined that the NPP of annual and perennial grasses, as well as HLI and SEI, were important predictors of field-measured litter biomass in 2018, with the model featuring a high overall fit (R2 = 0.61). Model transferability based on extrapolating the FMA predictive relationships from 2018 to the following years provided similar overall fits (R2 ≈ 0.5). The fire-free period had a significant effect on the litter biomass accumulation on rangelands within the study site, with greater litter biomass in areas where the fire-free period was