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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34

Greening of the Earth and its drivers

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system and provision of ecosystem services 1, 2 . Yet how global vegetation is responding to the changing environment is not well established. Here we use three long-term satellite leaf area index (LAI) records and ten global ecosystem models to investigate four key drivers of LAI trends during 1982 2009. We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models suggest that CO 2 fertilization effects explain 70% of the observed greening trend, followed by nitrogen deposition (9%), climate change (8%) and land cover change (LCC) (4%). CO 2 fertilization effects explain most of the greening trends in the tropics, whereas climate change resulted in greening of the high latitudes and the Tibetan Plateau. LCC contributed most to the regional greening observed in southeast China and the eastern United States. In conclusion, the regional effects of unexplained factors suggest that the next generation of ecosystem models will need to explore the impacts of forest demography, differences in regional management intensities for cropland and pastures, and other emerging productivity constraints such as phosphorus availability.

54 ENVIRONMENTAL SCIENCES↗

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

Soil Moisture↗

SNM Radiation Signature Classification Using Different Semi-Supervised Machine Learning Models

The timely detection of special nuclear material (SNM) transfers between nuclear facilities is an important monitoring objective in nuclear nonproliferation. Persistent monitoring enabled by successful detection and characterization of radiological material movements could greatly enhance the nuclear nonproliferation mission in a range of applications. Supervised machine learning can be used to signal detections when material is present if a model is trained on sufficient volumes of labeled measurements. However, the nuclear monitoring data needed to train robust machine learning models can be costly to label since radiation spectra may require strict scrutiny for characterization. Therefore, this work investigates the application of semi-supervised learning to utilize both labeled and unlabeled data. As a demonstration experiment, radiation measurements from sodium iodide (NaI) detectors are provided by the Multi-Informatics for Nuclear Operating Scenarios (MINOS) venture at Oak Ridge National Laboratory (ORNL) as sample data. Anomalous measurements are identified using a method of statistical hypothesis testing. After background estimation, an energy-dependent spectroscopic analysis is used to characterize an anomaly based on its radiation signatures. In the absence of ground-truth information, a labeling heuristic provides data necessary for training and testing machine learning models. Supervised logistic regression serves as a baseline to compare three semi-supervised machine learning models: co-training, label propagation, and a convolutional neural network (CNN). In each case, the semi-supervised models outperform logistic regression, suggesting that unlabeled data can be valuable when training and demonstrating value in semi-supervised nonproliferation implementations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Monitoring Coastal Marshes for Persistent Flooding and Salinity Stress

Our objective is to provide NASA remote sensing products that provide inundation and salinity information on an ecosystem level to support habitat switching models. Project born out of need by the Coastal Restoration Monitoring System (CRMS), joint effort by Louisiana Department of Natural Resources and the U.S. Geological Survey, for information on persistence of flooding by storm surge and other flood waters. The results of the this work support the habitat-switching modules in the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) model, which provides scientific evaluation for restoration management. CLEAR is a collaborative effort between the Louisiana Board of Regents, the Louisiana Department of Natural Resources (LDNR), the U.S. Geological Survey (USGS), and the U.S. Army Corps of Engineers (USACE). Anticipated results will use: a) Resolution enhanced time series data combining spatial resolution of Landsat with temporal resolution of MODIS for inundation estimates. b) Potential salinity products from radar and multispectral modeling. c) Combined inundation and salinity inputs to habitat switching module to produce habitat switching maps (shown at left)

Kalcic, Maria↗

On the Nature of Valence Charge and Spin Excitations via Multi-Orbital Hubbard Models for Infinite-Layer Nickelates

Building upon the recent progress on the intriguing underlying physics for the newly discovered infinite-layer nickelates, in this article we review an examination of valence charge and spin excitations via multi-orbital Hubbard models as way to determine the fundamental building blocks for Hamiltonians that can describe the low energy properties of infinite-layer nickelates. We summarize key results from density-functional approaches, and apply them to the study of x-ray absorption to determine the valence ground states of infinite-layer nickelates in their parent form, and show that a fundamental d 9 configuration as in the cuprates is incompatible with a self-doped ground state having holes in both d x 2 - y 2 and a rare-earth-derived axial orbital. When doped, we determine that the rare-earth-derived orbitals empty and additional holes form low spin (S = 0) d 8 Ni states, which can be well-described as a doped single-band Hubbard model. Using exact diagonalization for a 2-orbital model involving Ni and rare-earth orbitals, we find clear magnons at 1/2 filling that persist when doped, albeit with larger damping, and with a dependence on the precise orbital energy separation between the Ni- and rare-earth-derived orbitals. Taken together, a full two-band model for infinite-layer nickelates can well describe the valence charge and spin excitations observed experimentally.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Requirements for the early atmosphere of Mars from nitrogen isotope ratios

The N escape models of Fox and Dalgarno and Fox required the presence of a dense, early CO2 atmosphere to inhibit fractionation of the N isotopes N-15 and N-14. The computed photochemical escape fluxes are so large at the present that the isotope ratio measured by Viking (about 1.62x terrestrial) can be produced in about 1.5 b.y. This model was refined in several ways. It was updated to incorporate the variation of the escape fluxes with increases in the solar fluxes at earlier times according to the model of Zahnle and Walker. As expected, this exacerbates the problem with overfractionation, but not greatly. Most of the escape and fractionation of the N occurs in the last 1.5 b.y., when the solar flux was only slightly different from the present. The dense early atmosphere must persist only a bit longer in order to reproduce the measured isotope ratio. The model was also modified to take into account changes in the O mixing ratio with time in the past, assuming that the O abundance is proportional to the square root of the solar flux. Although the production rate of O from photodissociation of CO2 scales as the solar flux, the strength of the winds and other mixing processes also increases with the solar flux, resulting in possibly more effective transport of O to the lower atmosphere where it is destroyed by catalytic and three-body recombination mechanisms.

Fox, J. L.↗

New observational evidence for a positive cloud feedback that amplifies the Atlantic Multidecadal Oscillation

Abstract The Atlantic Multidecadal Oscillation (AMO) affects climate variability in the North Atlantic basin and adjacent continents with potential societal impacts. Previous studies based on model simulations and short‐term satellite retrievals hypothesized an important role for cloud radiative forcing in modulating the persistence of the AMO in the tropics, but this mechanism remains to be tested with long‐term observational records. Here we analyze data sets that span multiple decades and present new observational evidence for a positive feedback between total cloud amount, sea surface temperature (SST), and atmospheric circulation that can strengthen the persistence and amplitude of the tropical branch of the AMO. In addition, we estimate cloud amount feedback from observations and quantify its impact on SST with idealized modeling experiments. From these experiments we conclude that cloud feedbacks can account for 10% to 31% of the observed SST anomalies associated with the AMO over the tropics.

Bellomo, Katinka↗

A metabolomics and mouse models approach to study inflammatory and immune responses to radiation

The three-year project entitled "A Metabolomics and Mouse Models Approach to Study Inflammatory and Immune Responses to Radiation" was initiated in September 2009. The overall objectives of this project were to investigate the acute and persistent effects of low dose radiation on T cell lymphocyte function and physiology, as well the contributions of these cells to radiation-induced inflammatory responses. Inflammation after ionizing radiation (IR), even at low doses, may impact a variety of disease processes, including infectious disease, cardiovascular disease, cancer, and other potentially inflammatory disorders. There were three overall specific aims: 1. To investigate acute and persistent effects of low dose radiation on T cell subsets and function; 2. A genetic approach with mouse models to investigate p38 MAPK pathways that are involved in radiation-induced inflammatory signaling; 3. To investigate the effect of radiation quality on the inflammatory response. We have completed the work proposed in these aims.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

Evaluation↗

EVIDENCE FOR ACCRETION RATE CHANGE DURING TYPE I X-RAY BURSTS

The standard approach for time-resolved X-ray spectral analysis of thermonuclear bursts involves subtraction of the pre-burst emission as background. This approach implicitly assumes that the persistent flux remains constant throughout the burst. We reanalyzed 332 photospheric radius expansion bursts observed from 40 sources by the Rossi X-Ray Timing Explorer, introducing a multiplicative factor f{sub a} to the persistent emission contribution in our spectral fits. We found that for the majority of spectra the best-fit value of f{sub a} is significantly greater than 1, suggesting that the persistent emission typically increases during a burst. Elevated f{sub a} values were not found solely during the radius expansion interval of the burst, but were also measured in the cooling tail. The modified model results in a lower average value of the {chi}{sup 2} fit statistic, indicating superior spectral fits, but not yet to the level of formal statistical consistency for all the spectra. We interpret the elevated f{sub a} values as an increase of the mass accretion rate onto the neutron star during the burst, likely arising from the effects of Poynting-Robertson drag on the disk material. We measured an inverse correlation of f{sub a} with the persistent flux, consistent with theoretical models of the disk response. We suggest that this modified approach may provide more accurate burst spectral parameters, as well as offering a probe of the accretion disk structure.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparison of Meteoroid Flux Models for Near Earth Space

Over the last decade several new models for the sporadic interplanetary meteoroid flux have been developed. These include the Meteoroid Engineering Model (MEM), the Divine-Staubach model and the Interplanetary Meteoroid Engineering Model (IMEM). They typically cover mass ranges from 10-12 g (or lower) to 1 g and are applicable for model specific sun distance ranges between 0.2 A.U. and 10 A.U. Near 1 A.U. averaged fluxes (over direction and velocities) for all these models are tuned to the well established interplanetary model by Gr?n et. al. However, in many respects these models differ considerably. Examples are the velocity and directional distributions and the assumed meteoroid sources. In this paper flux predictions by the various models to Earth orbiting spacecraft are compared. Main differences are presented and analysed. The persisting differences even for near Earth space can be seen as surprising in view of the numerous ground based (optical, radar) and in-situ (captured IDPs, in-situ detectors and analysis of retrieved hardware) measurements and simulations. Remaining uncertainties and potential additional studies to overcome the existing model discrepancies are discussed.

Drolshagen, G.↗

A RECONNECTION-DRIVEN MODEL OF THE HARD X-RAY LOOP-TOP SOURCE FROM FLARE 2004 FEBRUARY 26

A compact X-class flare on 2004 February 26 showed a concentrated source of hard X-rays at the tops of the flare’s loops. This was analyzed in previous work and interpreted as plasma heated and compressed by slow magnetosonic shocks (SMSs) generated during post-reconnection retraction of the flux. That work used analytic expressions from a thin flux tube (TFT) model, which neglected many potentially important factors such as thermal conduction and chromospheric evaporation. Here we use a numerical solution of the TFT equations to produce a more comprehensive and accurate model of the same flare, including those effects previously omitted. These simulations corroborate the prior hypothesis that slow-mode shocks persist well after the retraction has ended, thus producing a compact, loop-top source instead of an elongated jet, as steady reconnection models predict. Thermal conduction leads to densities higher than analytic estimates had predicted, and evaporation enhances the density still higher, but at lower temperatures. X-ray light curves and spectra are synthesized by convolving the results from a single TFT simulation with the rate at which flux is reconnected, as measured through motion of flare ribbons, for example. These agree well with light curves observed by RHESSI and GOES and spectra from RHESSI . An image created from a superposition of TFT model runs resembles one produced from RHESSI observations. This suggests that the HXR loop-top source, at least the one observed in this flare, could be the result of SMSs produced in fast reconnection models like Petschek’s.

79 ASTRONOMY AND ASTROPHYSICS↗

HSRL-2 Observations of Aerosol Variability During an Aerosol Build-up Event in Houston and Comparisons With WRF-Chem

The NASA Langley airborne multi-wavelength High Spectral Resolution Lidar (HSRL-2) provides vertical distribution of aerosol optical properties as curtains of aerosol extinction, backscatter and depolarization along the flight track, plus intensive properties that are used to infer aerosol type and external mixing of types. Deployed aboard the NASA Langley King Air on the DISCOVER-AQ field mission in Houston in September 2013, HSRL-2 flew a pattern that included 18 ground sites, repeated four times a day, coordinated with a suite of airborne in situ measurements. The horizontally and vertically resolved curtains of HSRL-2 measurements give an unparalleled view of the spatial and temporal variability of aerosol, which provide broad context for interpreting other measurements and models. Detailed comparisons of aerosol extinction are made with the WRF-Chem chemical transport model along the HSRL-2 flight path. The period from Sept. 11-14 is notable for a large aerosol build-up and persistent smoke layers. We investigate the aerosol properties using the vertically resolved HSRL-2 measurements and aerosol typing analysis plus WRFChem model tracers and back trajectories, and modeling of humidification effects.

Burton, Sharon P.↗

Dynamically downscaled seasonal heat wave projections in the CONUS

Heat waves are a well-documented hazard that are projected to increase in intensity, duration, and frequency with climate change. Regions of the US experience widely varying temperatures; for example, 35 °C is extremely hot for spring in the Northeast but not for summer in the Southeast. It is important to evaluate projections within a regional context and at a high enough resolution to understand the risks to populations. We identify heat waves across the Conterminous US (CONUS) under SSP5–8.5 from 2020 to 2059 with an ensemble of dynamically downscaled Coupled Model Intercomparison Project Phase 6 (CMIP6) model outputs. We demonstrate that there are regional differences caused by seasonal and local drivers of persistent hot temperatures. Summer heat waves are increasing in intensity and duration faster than winter heat waves because of the atmospheric conditions that promote these events. Our analysis emphasizes the value of fine-resolution modeling for projecting future climate risks.

Rubin, Hannah [University of Tennessee, Knoxville ↗

Aroclor 1254, a developmental neurotoxicant, alters energy metabolism- and intracellular signaling-associated protein networks in rat cerebellum and hippocampus

The vast literature on the mode of action of polychlorinated biphenyls (PCBs) indicates that PCBs are a unique model for understanding the mechanisms of toxicity of environmental mixtures of persistent chemicals. PCBs have been shown to adversely affect psychomotor function and learning and memory in humans. Although the molecular mechanisms for PCB effects are unclear, several studies indicate that the disruption of Ca{sup 2+}-mediated signal transduction plays significant roles in PCB-induced developmental neurotoxicity. Culminating events in signal transduction pathways include the regulation of gene and protein expression, which affects the growth and function of the nervous system. Our previous studies showed changes in gene expression related to signal transduction and neuronal growth. In this study, protein expression following developmental exposure to PCB is examined. Pregnant rats (Long Evans) were dosed with 0.0 or 6.0 mg/kg/day of Aroclor-1254 from gestation day 6 through postnatal day (PND) 21, and the cerebellum and hippocampus from PND14 animals were analyzed to determine Aroclor 1254-induced differential protein expression. Two proteins were found to be differentially expressed in the cerebellum following PCB exposure while 18 proteins were differentially expressed in the hippocampus. These proteins are related to energy metabolism in mitochondria (ATP synthase, sub unit {beta} (ATP5B), creatine kinase, and malate dehydrogenase), calcium signaling (voltage-dependent anion-selective channel protein 1 (VDAC1) and ryanodine receptor type II (RyR2)), and growth of the nervous system (dihydropyrimidinase-related protein 4 (DPYSL4), valosin-containing protein (VCP)). Results suggest that Aroclor 1254-like persistent chemicals may alter energy metabolism and intracellular signaling, which might result in developmental neurotoxicity. -- Highlights: Black-Right-Pointing-Pointer We performed brain proteomic analysis of rats exposed to the neurotoxicant, Aroclor 1254. Black-Right-Pointing-Pointer Cerebellum and hippocampus were analyzed by 2D DIGE and Mass spectrometry. Black-Right-Pointing-Pointer Proteins affected participate in Energy metabolism, calcium signaling and nervous system growth.

60 APPLIED LIFE SCIENCES↗

Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage

Data acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Collider, the experiments at CERN need to meet challenging requirements to record data with a much higher occupancy in the detectors. The DAQ system will receive and deliver data with a significantly increased trigger rate, one million events per second, and capacity, terabytes of data per second. An effective way to meet these requirements is to decouple real-time data acquisition from event selection. Data fragments can be temporarily stored in a large distributed key-value store. Fragments belonging to the same event can be then queried on demand, by the data selection processes. Implementing such a model relies on a proper combination of emerging technologies, such as persistent memory, NVMe SSDs, scalable networking, and data structures, as well as high performance, scalable software. In this paper, we present DAQDB (Data Acquisition Database) — an open source implementation of this design that was presented earlier, with an extensive evaluation of this approach, from the single node to the distributed performance. Furthermore, we complement our study with a description of the challenges faced and the lessons learned while integrating DAQDB with the existing software framework of the ATLAS experiment.

Abed Abud, Adam↗

Dynamical resilience to disorder: The dilute Hubbard model on the Lieb lattice

In itinerant systems, electron-electron interactions may lead to the formation of local magnetic moments and their effective exchange coupling, which in turn gives rise to long-range magnetic order. Therefore, when moment formation is weakened, such as in the single-band Hubbard model on a square lattice with the on-site repulsion being randomly switched off on a fraction $\textit{x}$ of sites, magnetic order is suppressed beyond some critical $x_c$, which was found to lie below the classical percolation threshold $x^{\text{(perc,sq)}}_c$. Here we study dilute magnetism in flat band systems, namely, in the Hubbard model on a “Lieb” lattice. Interestingly, we show that magnetic order persists to x almost twice as large as the classical percolation threshold for the lattice, thus emphasizing the central role of electron itinerancy to the magnetic response. Further, the analysis of the orbital-resolved order parameters reveals that the contribution of the fourfold coordinated $\textit{“d”}$ sites to magnetism is dramatically affected by dilution, while the localized $\textit{“p”}$ states of the flat band provide the dominant contribution to long-range correlations. We also examine the transport properties, which suggest the existence of an insulator-to-metal transition in the same range of the critical magnetic dilution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

$\mathscr{PT}$ symmetry enforced twin exchange as the origin of chirality-induced spin selectivity

Chiral molecules, ubiquitous in chemistry and biology, can differentiate electrons by their spin, a phenomenon known as chirality-induced spin selectivity (CISS). Despite its robustness and technological relevance, CISS has resisted conventional explanation: Spin-orbit coupling (SOC) models cannot fully account for the observed magnitude, room-temperature persistence, or equilibrium signatures. Here, we argue that structural chirality enforces a twin-pair exchange mechanism via the indistinguishability principle, which intrinsically couples spin and spatial degrees of freedom such that wave functions cannot be factorized into spin and spatial components. We derive an effective Hamiltonian that describes both transport and equilibrium CISS phenomena and is non-Hermitian. However, the inherent pseudo-Hermiticity, with $\mathscr{PT}$ symmetry as a special case, ensures real eigenvalues and thermodynamic consistency. We demonstrate that our framework is a step toward resolving long-standing anomalies of CISS. It situates CISS alongside equilibrium symmetry-breaking phenomena such as ferromagnetism and superconductivity, with implications for spintronics, catalysis, and the origins of biological homochirality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗