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At least 865 records · Page 48

Easy Meal

The woman pictured below is sitting down to a nutritious, easily-prepared meal similar to those consumed by Apollo astronauts. The appetizing dishes shown were created simply by adding water to the contents of a Mountain House* Easy Meal package of freeze dried food. The Easy Meal line is produced by Oregon Freeze Dry Foods, Inc., Albany, Oreaon, a pioneer in freeze drying technology and a company long associated with NASA in developing suitable preparations for use on manned spacecraft. Designed to provide nutritionally balanced, attractive hot meals for senior adults, Easy Meal is an offshoot of a 1975-77 demonstration project managed by Johnson Space Center and called Meal System for the Elderly. The project sought ways to help the estimated 3.5 million elderly Americans who are unable to take advantage of existing meal programs. Such services are provided by federal, state and local agencies, but they are not available to many who live in rural areas, or others who are handicapped, temporarily ill or homebound for other reasons. Oregon Freeze Dry Foods was a participant in that multi-agency cooperative project. With its Easy Meal assortment of convenience foods pictured above left, the company is making commercially available meal packages similar to those distributed in the Meal System for the Elderly program. In the freeze drying process, water is extracted from freshly-cooked foods by dehydration at very low temperatures, as low as 50 I degrees below zero. Flavor is locked in by packaging the dried food in pouches which block out moisture and oxygen, the principal causes of food deterioration; thus the food can be stored for long periods without refrigeration. Meals are reconstituted by adding hot or cold water, depending on the type of food, and they are table ready in five to 10 minutes. Oregon Freeze Dry Foods offers five different meal packages and plans to expand the line.

Source record↗

Jet substructure from dark sector showers

We examine the robustness of collider phenomenology predictions for a dark sector scenario with QCD-like properties. Pair production of dark quarks at the LHC can result in a wide variety of signatures, depending on the details of the new physics model. A particularly challenging signal results when prompt production induces a parton shower that yields a high multiplicity of collimated dark hadrons with subsequent decays to Standard Model hadrons. The final states contain jets whose substructure encodes their non-QCD origin. This is a relatively subtle signature of strongly coupled beyond the Standard Model dynamics, and thus it is crucial that analyses incorporate systematic errors to account for the approximations that are being made when modeling the signal. We estimate theoretical uncertainties for a canonical substructure observable designed to be sensitive to the gauge structure of the underlying object, the two-point energy correlator $ {e}_2^{\left(\beta \right)} $ , by computing envelopes between resummed analytic distributions and numerical results from Pythia. We explore the separability against the QCD background as the confinement scale, number of colors, number of flavors, and dark quark masses are varied. Additionally, we investigate the uncertainties inherent to modeling dark sector hadronization. Simple estimates are provided that quantify one’s ability to distinguish these dark sector jets from the overwhelming QCD background. Such a search would benefit from theory advances to improve the predictions, and the increase in statistics using the data to be collected at the high luminosity LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Climate-Driven Limits to Future Carbon Storage in California's Wildland Ecosystems

Enhanced ecosystem carbon storage is a key component of many climate mitigation pathways. The State of California has set an ambitious goal of carbon neutrality by 2045, relying in part on enhanced carbon sequestration in natural and working lands. We used statistical modeling, including random forest and climate analog approaches, to explore the climate-driven challenges and uncertainties associated with the goal of long-term carbon sequestration in forests and shrublands. We found that seasonal patterns of temperature and precipitation are strong controllers of the spatial distribution of aboveground live carbon. RCP8.5 projections of temperature and precipitation are estimated to drive decreases of 16.1% ± 7.5% in aboveground live carbon by the end of the century, with coastal areas of central and northern California and low/mid-elevation mountain areas being most vulnerable. With RCP4.5 projections, declines are less severe, with 8.8% ± 5.3% carbon loss. In either scenario, increases in temperature systematically cause biomass declines, and the spread of projected precipitation across 32 CMIP5 models contributes to substantial uncertainty in the magnitude of that decline. Projected changes in the environmental niche for the 20 most biomass-dominant tree species revealed widespread replacement of conifers by oak species in low elevation regions of central and northern California, with a corresponding decline in carbon storage depending on expected migration rates. The spatial patterns of vulnerability we identify may allow policymakers to assess where carbon sequestration in aboveground biomass is an appropriate part of a climate mitigation portfolio, and where future climate-driven carbon losses may be a liability.

54 ENVIRONMENTAL SCIENCES↗

Calculation of radiative properties of nonequilibrium hydrogen plasma

A computer program called NEQRAP is described that calculates the radiative properties of nonequilibrium ionized hydrogen. From the given electron temperature, electron density, and atom density values (which do not necessarily satisfy the equilibrium relationship) and intensities of incident radiation, the non-Boltzmann populations of electronic states are computed by solving the equation of quasi-steady-state population distribution. Emission and absorption coefficients are determined as functions of wavelength by invoking the principle of detailed balance between the upper and lower states of each radiative transition. Radiative transport through the medium is computed assuming a one-dimensional uniform slab. The rate of ionic reaction is also computed. When used on a sample case, the program shows that there is a large difference between the calculated intensities of radiation emitted by a bulk of equilibrium and nonequilibrium hydrogen. The accuracy of the program is estimated to be better than 10%.

Park, C.↗

Remotely-Sensed Regional-Scale Evapotranspiration of a Semi-Arid Great Basin Desert and its Relationship to Geomorphology, Soils, and Vegetation

Landsat thematic mapper data are used to estimate instantaneous regional-scale surface water and energy fluxes in a semi-arid Great Basin desert of the western United States. Results suggest that it is possible to scale from point measurements of environmental state variables to regional estimates of water and energy exchange. This research characterizes the unifying thread in the classical climate-topography-soil-vegetation relation -the surface water and energy balance-through maps of the partitioning of energy throughout the landscape. The study was conducted in Goshute Valley of northeastern Nevada, which is characteristic of most faulted graben valleys of the Basin and Range Province of the western United States. The valley comprises a central playa and lake plain bordered by alluvial fans emanating from the surrounding mountains. The distribution of evapotranspiration (ET) is lowest in the middle reaches of the fans where the water table is deep and plants are small, resulting in low evaporation and transpiration. Highest ET occurs in the center of the valley, particularly in the playa, where limited to no vegetation occurs, but evaporation is relatively high because of a shallow water table and silty clay soil capable of large capillary movement. Intermediate values of ET are associated with large shrubs and is dominated by transpiration.

Laymon, C.↗

Estimating Single-Trial Responses in EEG

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

Shah, A. S.↗

An Empirical State Error Covariance Matrix for Batch State Estimation

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty. Also, in its most straight forward form, the technique only requires supplemental calculations to be added to existing batch algorithms. The generation of this direct, empirical form of the state error covariance matrix is independent of the dimensionality of the observations. Mixed degrees of freedom for an observation set are allowed. As is the case with any simple, empirical sample variance problems, the presented approach offers an opportunity (at least in the case of weighted least squares) to investigate confidence interval estimates for the error covariance matrix elements. The diagonal or variance terms of the error covariance matrix have a particularly simple form to associate with either a multiple degree of freedom chi-square distribution (more approximate) or with a gamma distribution (less approximate). The off diagonal or covariance terms of the matrix are less clear in their statistical behavior. However, the off diagonal covariance matrix elements still lend themselves to standard confidence interval error analysis. The distributional forms associated with the off diagonal terms are more varied and, perhaps, more approximate than those associated with the diagonal terms. Using a simple weighted least squares sample problem, results obtained through use of the proposed technique are presented. The example consists of a simple, two observer, triangulation problem with range only measurements. Variations of this problem reflect an ideal case (perfect knowledge of the range errors) and a mismodeled case (incorrect knowledge of the range errors).

Frisbee, Joseph H., Jr.↗

Continuous Baseline Microphysical Retrieval (MICROBASE) Value-Added Product Report

This technical report describes the Continuous Baseline Microphysical Retrieval (MICROBASE) Value-Added Product (VAP) produced operationally by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility. MICROBASE provides a continuous estimate of cloud microphysical properties at ARM fixed observatories and ARM Mobile Facility (AMF) sites. It is designed to run operationally and provide data to the ARM Data Center for scientific distribution. This technical report presents an overview of the VAP as a resource for data users and ongoing records for major updates to these products.

54 ENVIRONMENTAL SCIENCES↗

Results of a comprehensive atmospheric aerosol-radiation experiment in the southwestern United States. I - Size distribution, extinction optical depth and vertical profiles of aerosols suspended in the atmosphere. II - Radiation flux measurements and

Results are reported for a field test that was aimed at acquiring a sufficient set of measurements of aerosol properties required as input for radiative-transfer calculations relevant to the earth's radiation balance. These measurements include aerosol extinction and size distributions, vertical profiles of aerosols, and radiation fluxes. Physically consistent, vertically inhomogeneous models of the aerosol characteristics of a turbid atmosphere over a desert and an agricultural region are constructed by using direct and indirect sampling techniques. These results are applied for a theoretical interpretation of airborne radiation-flux measurements. The absorption term of the complex refractive index of aerosols is estimated, a regional variation in the refractive index is noted, and the magnitude of solar-radiation absorption by aerosols and atmospheric molecules is determined.

Deluisi, J. J.↗

Areal interpolation of population projections consistent with different SSPs from 1-km resolution to block level based on USA Structures dataset

Population data are normally collected at various census administrative levels, and areal interpolation of population is often required to transform population to the desired spatial resolution. Building footprint datasets, such as Microsoft building footprints, have proven to be useful in estimating population distribution and can therefore be used for areal interpolation of population. In addition to Microsoft building footprints, the recently released USA Structures dataset provides additional information such as building type and building height for some regions, which may provide valuable information for a better depiction of population distribution and improved population areal interpolation accuracy. In this study, we have conducted areal interpolation of population projections consistent with three different Shared Socioeconomic Pathways (SSP2, SSP3, and SSP5) from 1-km grid cells to block level in Washington state for every ten years from 2020 to 2040 based on USA Structures. We assessed USA Structures-based population downscaling accuracy using U.S. decennial survey data in 2020 under three different downscaling schemes, including population downscaling from census tracts to block groups, from census tracts to blocks, and from block groups to blocks. The resulting accuracies were compared with those based on Microsoft building footprints. The comparison showed that USA Structures achieved higher accuracies across different population density regions and areas with different urbanization extent within our study area.

99 GENERAL AND MISCELLANEOUS↗

Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning

Quantum error mitigation (QEM) is critical in reducing the impact of noise in the pre-fault-tolerant era, and is expected to complement error correction in fault-tolerant quantum computing (FTQC). In this work, we propose a novel QEM approach, Q-Cluster, that uses unsupervised learning (clustering) to reshape the measured bit-string distribution. Our approach starts with a simplified bit-flip noise model. It first performs clustering on noisy measurement results, i.e., bit-strings, based on the Hamming distance. The centroid of each cluster is calculated using a qubit-wise majority vote. Next, the noisy distribution is adjusted with the clustering outcomes and the bitflip error rates using Bayesian inference. Our simulation results show that Q-Cluster can mitigate high noise rates (up to 40% per qubit) with the simple bit-flip noise model. However, real quantum computers do not fit such a simple noise model. To address the problem, we (a) apply Pauli twirling to tailor the complex noise channels to Pauli errors, and (b) employ a machine learning model, ExtraTrees regressor, to estimate an effective bit-flip error rate using a feature vector consisting of machine calibration data (gate & measurement error rates), circuit features (number of qubits, numbers of different types of gates, etc.) and the shape of the noisy distribution (entropy). Our experimental results show that our proposed Q-Cluster scheme improves the fidelity by a factor of 1.46x, on average, compared to the unmitigated output distribution, for a set of low-entropy benchmarks on five different IBM quantum machines. Our approach outperforms the state-of-art QEM approaches RZNE [28], M3 [24], Hammer [35], and QBEEP [33] by 1.26x,1.29x,1.47x, and 2.65 x, respectively.

42 ENGINEERING↗

Remotely-Sensed Regional-Scale Evapotranspiration of a Semi-Arid Great Basin Desert and its Relationship to Geomorphology, Soils, and Vegetation

Landsat Thematic Mapper data is used to estimate instantaneous regional-scale surface water and energy fluxes in a semi-arid Great Basin desert of the western United States. Results suggest that it is possible to scale from point measurements of environmental state variables to regional estimates of water and energy exchange. This research characterizes the unifying thread in the classical climate-topography-soil-vegetation relation-the surface water and energy balance-through maps of the partitioning of energy throughout the landscape. The study was conducted in Goshute Valley of northeastern Nevada, which is characteristic of most faulted graben valleys of the Basin and Range Province of the western United States. The valley comprises a central playa and lake plain bordered by alluvial fans emanating from the surrounding mountains. The distribution of evapotranspiration (ET) is lowest in the middle reaches of the fans where the water table is deep and plants are small, resulting in low evaporation and transpiration. Highest ET occurs in the center of the valley, particularly in the playa, where limited to no vegetation occurs, but evaporation is relatively high because of a shallow water table and silty clay soil capable of large capillary movement. Intermediate values of ET are associated with large shrubs and is dominated by transpiration.

Laymon, C.↗

Latent Heating from TRMM Satellite Measurements

Rainfall production is a fundamental process within the Earth;s hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations with the Tropics - as well as modify the energetic efficiencies of mid-latitude weather systems. This paper highlights the retrieval of observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional amount of rainfall over the global Tropics and sub-tropics - information which can be used to estimate the spacetime structure of latent heating across the Earth's low latitudes. A set of algorithm methodologies has and continues to be developed to estimate latent heating based on rain rate profile retrievals obtained from TRMM measurements. These algorithms are briefly described followed by a discussion of the foremost latent heating products that can be generate from them. The investigation then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

Tao, W.-K.↗

An Approach for the Long-Term 30-m Land Surface Snow-Free Albedo Retrieval from Historic Landsat Surface Reflectance and MODIS-based A Priori Anisotropy Knowledge

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a "MODIS-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with MODIS Bidirectional Reflectance Distribution Function (BRDF) information. Here we present a "pre-MODIS era" approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT reflects a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from MODIS observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir reflectance ratios as a bridge between the Landsat and MODIS scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes.We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach respectively with that from the "concurrent" approach and the coincident MODIS operational surface albedo products. Using the tower measurements as reference, the derived Landsat 30-m snow-free shortwave broadband albedo yields an absolute accuracy of 0.02 with a root mean square error less than 0.016 and a bias of no more than 0.007. A further cross-comparison over individual scenes shows that the retrieved white sky shortwave albedo from the "pre-MODIS era" LUT approach is highly consistent (R(exp 2) = 0.988, the scene-averaged low RMSE = 0.009 and bias = −0.005) with that generated by the earlier "concurrent" approach. The Landsat albedo also exhibits more detailed landscape texture and a wider dynamic range of albedo values than the coincident 500-m MODIS operational products (MCD43A3), especially in the heterogeneous regions. Collectively, the "pre-MODIS" LUT and "concurrent" approaches provide a practical way to retrieve long-term Landsat albedo from the historic Landsat archives as far back as the 1980s, as well as the current Landsat-8 mission, and thus support investigations into the evolution of the albedo of terrestrial biomes at fine resolution.

Albedo algorithm↗

Search for resonant production of dark quarks in the dijet final state with the ATLAS detector

This paper presents a search for a new Z' resonance decaying into a pair of dark quarks which hadronise into dark hadrons before promptly decaying back as Standard Model particles. This analysis is based on proton-proton collision data recorded at $\sqrt{s}$ = 13 TeV with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to an integrated luminosity of 139 fb –1 . After selecting events containing large-radius jets with high track multiplicity, the invariant mass distribution of the two highest-transverse-momentum jets is scanned to look for an excess above a data-driven estimate of the Standard Model multijet background. No significant excess of events is observed and the results are thus used to set 95% confidence-level upper limits on the production cross-section times branching ratio of the Z' to dark quarks as a function of the Z' mass for various dark-quark scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Diffusion coefficients predicting facet-dependent crystallization in amorphous silicon nitride

Amorphous silicon nitride is a common material in microelectronics devices, which acts as an insulating barrier. Extended annealing times at elevated temperature can initiate crystallization of α-Si 3 ⁢ N 4 , which does not possess the same barrier properties. Molecular dynamics can resolve the fundamental mechanism for α-Si 3 ⁢N 4 crystallization and the influence of local environments. Here, we compare two interatomic potentials and conclude that these models predict structural features (e.g., angular distributions and densities) which span the range of experimental measurements. We confirmed these models reproduce experimental estimates of activation energy and leveraged these models to identify crystallization drivers. We conclude that near-T g , facet-dependent silicon nitride crystal growth rates can be predicted directly by either bulk or interfacial diffusion properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Preserving nonlinear constraints in variational flow filtering data assimilation

Data assimilation aims to estimate the states of a dynamical system by optimally combining sparse and noisy observations of the physical system with uncertain forecasts produced by a computational model. The states of many dynamical systems of interest obey nonlinear physical constraints, and the corresponding dynamics is confined to a certain sub-manifold of the state space. Standard data assimilation techniques applied to such systems yield posterior states lying outside the manifold, violating the physical constraints. This work focuses on particle flow filters which use stochastic differential equations to evolve state samples from a prior distribution to samples from an observation-informed posterior distribution. The variational Fokker-Planck (VFP)—a generic particle flow filtering framework—is extended to incorporate non-linear, equality state constraints in the analysis. To this end, two algorithmic approaches that modify the VFP stochastic differential equation are discussed: (i) VFPSTAB, to inexactly preserve constraints with the addition of a stabilizing drift term, and (ii) VFPDAE, to exactly preserve constraints by treating the VFP dynamics as a stochastic differential-algebraic equation (SDAE). Additionally, an implicit-explicit time integrator is developed to evolve the VFPDAE dynamics. The strength of the proposed approach for constraint preservation in data assimilation is demonstrated on three test problems: the double pendulum, Korteweg-de-Vries, and the incompressible Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗

A framework for feasibility-level validation of high-resolution wave hindcast models

The value of long-term wave hindcasts for investigating wave climates, wave energy resources, and extreme wave conditions has motivated research developing, calibrating and validating wave hindcast models. Past hindcast model validation studies examined the accuracy in modeling bulk wave parameters of overall sea states without considering the dependency of the model's skill within different sea states. In the present study, a framework for wave hindcast model validation is developed by examining the model accuracy for the most frequently occurring sea states, sea states contributing the most energy to total wave power, sea states associated with hurricane events, and those with the largest model error. Here, validations using bulk wave parameters and frequency-directional spectra at these key sea states and extreme wave conditions based on univariate and bivariate-contour methods provide insights to improve model accuracy, identifying the model's strong and weak points, and pathways for improvement, e.g., modeling wave-current interactions and adjusting wind data. This study adds to a growing body of research demonstrating that a carefully calibrated and verified spectral wave hindcast model can be used to estimate key wave energy parameters over a wide range of wave energy climates, as well as their spatial, temporal, frequency, directional, and probabilistic distributions.

54 ENVIRONMENTAL SCIENCES↗