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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Drivers of Medicare Spending: A 15-Year Review of Radiation Oncology Charges Allowed by the Medicare Physician/Supplier Fee-for-Service Program Compared With Other Specialties

In 2019, the Centers for Medicare and Medicaid Services proposed a new radiation oncology alternative payment model aimed at reducing expenditures. We examined changes in aggregate physician Medicare charges allowed per specialty to provide contemporary context to proposed changes and hypothesize that radiation oncology charges remained stable through 2017.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Crystallization pathways and interfacial drivers for the formation of hierarchical architectures

The development of structural hierarchy on various length scales during crystallization process is ubiquitous in biological systems and is also observed in synthetic nanomaterials. The driving forces for the formations of complex architectures range from local interfacial interactions, that modify interfacial speciation, local supersaturation, and nucleation barriers, to macroscopic interparticle forces. Although it is enticing to interpret the formation of hierarchical architectures as the assembly of independently nucleated building blocks, often crystallization pathways follow monomer-by-monomer addition with structural complexity arising from interfacial chemical coupling and strongly correlated fluctuation dynamics in the electric double layers. Here, the mechanism of the development of structural hierarchy through heterogeneous nucleation, coupled interfacial nucleation and assembly, and oriented attachment of independently nucleated particles is discussed. In this article, the emphasis is made on the discussion of the underlying interfacial forces and chemical coupling that drives crystallization pathways towards the formation of structural hierarchy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Explaining drivers of housing prices with nonlinear hedonic regressions

Housing markets play a critical role in shaping the spatial and demographic evolution of urban areas. Simulating housing price dynamics can enhance projections of future urban development outcomes. However, traditional hedonic regressions for housing prices, which neglect nonlinear interactions among explanatory variables, often exhibit limited predictive performance. While machine learning (ML) methods can provide a more flexible representation of the relationships between predictors, they are often regarded as “black boxes” due to their complexity and lack of transparency. Interpretable ML techniques provide a promising route by combining the flexibility of ML methods with approaches to analyze the relationships between inputs and outputs. In this study, we employ interpretable ML to analyze the patterns driving the housing market in Baltimore, Maryland, USA. We train an Artificial Neural Network (ANN) to predict Baltimore housing prices based on structural characteristics (e.g., home size, number of stories) and locational attributes (e.g., distance to the city center). We then conduct sensitivity and Partial Dependence Plot (PDP) analyses to interpret the fitted ANN model. We find that the ML model achieves higher predictive accuracy and explains 16 % more of housing price variance than a traditional linear regression model. The interpretable ML model also reveals more nuanced and realistic nonlinear relationships between housing sales price and predictors as well as interactive effects underlying Baltimore home price dynamics. For instance, while the linear model indicates a steady housing price increase over time, our interpretable ML model detects a post-2008 decline, with smaller properties experiencing the sharpest drop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Soil compartments (bulk soil, litter, root and rhizosphere) as main drivers of soil protistan communities distribution in forests with different nitrogen deposition

Protists, in particular bacterivores, are essential players in the rhizosphere; thus, how their interactions with bacteria and fungi affect plant productivity and soil nutrient cycles warrants more attention. Using next-generation sequencing of the 18 S rRNA gene, we investigated the distribution of two major protistan phyla, Cercozoa and Endomyxa, across four seasons, and four soil compartments - rhizosphere, root, soil and litter. The sampling was replicated in two forests in Norway and the Czech Republic, in order to test our results across biogeographic scales. Compartment had a major influence in shaping protistan communities, over and above spatial distance and seasonal variation. Protistan diversity was highest in the bulk soil while lowest in the roots, suggesting that the plants select for restricted assemblages of protists. Accordingly, only the root compartment harboured a subset of the bulk soil protistan diversity. In addition, protistan communities showed markedly different distributions according to their feeding modes, with opposite patterns for bacterivores versus omnivores and eukaryvores. The small bacterivorous flagellates (mostly Glissomonadida) were more abundant in roots, while the larger amoeboid eukaryvores (e.g. some of the Cryomonadida and vampyrellids) dominated in soil and in the rhizosphere, and the omnivores (e.g. Euglyphida and part of the Cercomonadida), also large and mostly amoeboid, were more abundant in litter. The current view of the soil microbiome is mostly focused on bacteria and fungi: this detailed study on the community distribution of protists according to their feeding modes reveals the essential role they play in each of the soil compartments, an essential precondition for a detailed understanding of the soil food web and nutrient cycling in forest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Warming, permafrost thaw and increased nitrogen availability as drivers for plant composition and growth across the Tibetan Plateau

Permafrost-affected ecosystems are subject to warming and thawing, which can increase the availability of subsurface nitrogen (N) with consequences in otherwise N-limited tundra and alpine vegetation. Here, we quantify the extent of warming and permafrost thawing and the corresponding effects on nitrogen availability and plant growth based on a 20-year survey across 14 sites on the Tibetan Plateau. The survey showed that most sites have been subject to warming and thawing and that the upper permafrost zone across all sites was rich in inorganic N, mainly as ammonium. We further explore the efficiency of plants to utilize 15 N-labelled inorganic N over five years following 15 N addition at the permafrost table far below the main root zone. The 15 N experiment showed that deep-rooted plant species were able to utilize the labelled N. A SEM model suggests that changes in vegetation can be explained by both active layer warming and permafrost thawing and the associated changes in inorganic nitrogen availability. Our results highlight a feedback mechanism of climate warming, in which released plant-available N may favour deep-rooted plants. This can explain important changes in plant composition and growth across the sites on the Tibetan Plateau.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Integrin alpha 6 as a stemness driver is a novel promising target for HPV (+) head and neck squamous cell carcinoma

Although the incidence rates of head and neck squamous cell carcinoma (HNSCC) associated with human papilloma virus (HPV) infection have recently been on the rise, the underlying mechanism of its tumorigenesis remains largely unknown. Here, we investigated whether HNSCC cells with high expression of integrin alpha 6 (ITGα6), one of the HPV receptors, have a preference during HPV infection. In addition, we examined the gain or loss of function of the ITGα6 gene in HPV + ve HNSCC cells, as well as its prognostic value in patients with HNSCC. HPV pseudovirus was found to be more infective, with HNSCC cells featuring an overexpressed ITGα6 gene compared to the control cells. Overexpression and suppression of ITGα6 respectively increases and decreases stemness phenotypes of HPV + ve HNSCC cells. Furthermore, ITGα6 can regulate stemness by partially mediating AKT pathway in HPV + ve HNSCC cells. Finally, patients with HPV + ve HNSCC had a poor prognosis in cases of elevated ITGα6 expression; however, the expression levels of ITGα6 did not influence the survival rates of HPV-negative HNSCC patients. In conclusion, ITGα6 can serve as a potential therapeutic target for HPV + ve HNSCC cancer-like stem cells (CSCs).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Supply and Demand Drivers of Global Hydrogen Deployment in the Transition toward a Decarbonized Energy System

The role of hydrogen in energy system decarbonization is being actively examined by the research and policy communities. We evaluate the potential ‘hydrogen economy’ in global climate change mitigation scenarios using the Global Change Analysis Model (GCAM). We consider major hydrogen production methods in conjunction with delivery options to understand how hydrogen infrastructure affects its deployment. We also consider a rich set of hydrogen end-use technologies and vary their costs to understand how demand technologies affect deployment. We find that the availability of hydrogen transmission and distribution infrastructure primarily affects the hydrogen production mix, particularly the share produced centrally versus onsite, whereas assumptions about end-use technology primarily affect the scale of hydrogen deployment. In effect, hydrogen can be a distributed energy vector, enabled by onsite renewable electrolysis and, to a lesser extent, by onsite industrial production using natural gas with carbon capture and storage (CCS). While the share of hydrogen in final energy is small relative to the share of other major energy carriers in our scenarios, hydrogen enables decarbonization in difficult-to-electrify end uses such as industrial high-temperature heat. Its contribution to greenhouse gas mitigation increases as the climate objective is tightened.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Drivers of Water Use in the Agricultural Sector of the European Union 27

Population growth and the uncertain hazards that accompany climate change have put increasing pressure on the management and sustainability of water. It has a direct impact on agriculture and its domestic and international supply chain linkages. As one of the largest agricultural producers in the world, the European Union (EU) is particularly sensitive to changes in water availability. Therefore, here we perform a structural decomposition analysis based on the recently released EXIOBASE 3 database to examine in depth how changes in water input coefficients, in final demand and in technology have affected changes in water use across crops. Crop production consumes 99% of the direct water in agriculture. Our results show that the largest EU crop producers have experienced an increase in water use that is mostly driven by changes in technology. On the other hand, several Mediterranean countries, where water scarcity has been a problem for years, have decreased their water consumption mostly thanks to an improvement in their water intensity. Results by crop are consistent with those at the aggregated level except for vegetables of which water use changes have been primarily driven by changes in final demand and water intensity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Medium-Range Structural Order as the Driver of Activated Dynamics and Complexity Reduction in Glass-Forming Liquids

Here, we analyze in depth the Elastically Collective Nonlinear Langevin Equation theory of activated dynamics in metastable liquids to establish that the predicted inter-relationships between the alpha relaxation time, local cage and collective elastic barriers, dynamic localization length, and shear modulus are causally related within the theory to the medium range order (MRO) static correlation length. The latter grows exponentially with density for metastable hard sphere fluids and as a nonuniversal inverse power law with temperature for supercooled liquids under isobaric conditions. The physical origin of predicted connections between the alpha time and other metrics of cage order and the thermodynamic inverse dimensionless compressibility is fully established. It is discovered that although kinetic constraints from the real space first coordination shell are important for the alpha time, they are of secondary importance compared to the consequences of the more universal MRO correlations in both the modestly and deeply metastable regimes. This understanding sheds new light on the theoretical basis for, and prior successes of, the predictive mapping of chemically complex thermal liquids to effective hard sphere fluids based on matching their dimensionless compressibilities, a scheme we call “complexity reduction”. In essence, the latter is equivalent to the physical requirement that the thermal liquid MRO correlation equals that of its effective hard sphere analog. The mapping alone is shown to provide a remarkable level of quantitative predictive power for the glass transition temperature T g of 21 molecular and polymer liquids. Predictions for the chemically specific absolute magnitude and growth with cooling of the MRO correlation length are obtained and lie in the window of 2–6 nm at T g . Dynamic heterogeneity, elastic facilitation, and beyond pair structure issues are briefly discussed. Future opportunities to theoretically analyze the equilibrated deep glass regime are outlined.

cancer↗
DOE OSTI2023

Chemical and Physical Drivers for Improvement in Permeance and Stability of Linker-Free Graphene Oxide Membranes

Graphene oxide (GO) is a promising membrane material for chemical separations, including water treatment. However, GO has often required postsynthesis chemical modifications, such as linkers or intercalants, to improve either the permeability, performance, or mechanical integrity of GO membranes. In this work, we explore two different feedstocks of GO to investigate chemical and physical differences, where we observe up to a 100× discrepancy in the permeability–mass loading trade-off while maintaining nanofiltration capacity. GO membranes also show structural stability and chemical resilience to harsh pH conditions and bleach treatment. Here we probe GO and the resulting assembled membranes through a variety of characterization approaches, including a novel scanning-transmission-electron-microscopy-based visualization approach, to connect differences in sheet stacking and oxide functional groups to significant improvements in permeability and chemical stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Varying Contributions of Drivers to the Relationship Between Canopy Photosynthesis and Far‐Red Sun‐Induced Fluorescence for Two Maize Sites at Different Temporal Scales

Abstract Sun‐induced fluorescence (SIF) has been found to be strongly correlated with gross primary production (GPP) in a quasi‐linear pattern at the scales beyond leaves. However, the causes of the GPP:SIF relationship deviating from a linear pattern remain unclear. In the current study conducted at two maize sites in Nebraska in 2017 summer growing season, we investigated the relationship between GPP and SIF at 760 nm (F 760 ) at two temporal scales and quantified the contributions of incoming photosynthetically active radiation (PAR in ), fraction of absorbed PAR (fPAR), light use efficiency (LUE), and F 760 yield (F 760,y , defined as F 760 /(PAR in ×fPAR)) to GPP and F 760 variabilities to further understand the linearity and deviations in the GPP:F 760 relationship. We found the following: (1) For individual growth stages when canopy structure and chlorophyll content were stable, GPP and F 760 were strongly controlled by PAR in , while LUE and F 760,y had much lower contributions to the GPP:F 760 relationship; during this period, LUE and F 760,y had either a slightly negative or no clear relationship, which explained some deviations in the GPP:SIF relationship. (2) At the seasonal scale, the contribution of LUE to GPP variability as well as the contribution of F 760,y to F 760 variability increased and was comparable to the contribution of PAR in ; the LUE:F 760,y relationship showed a strong linear relationship, which strengthened the linear GPP:F 760 relationship. Both maize sites showed similar patterns. A framework was applied to estimate LUE at individual stages and as a result, significantly improved the GPP estimation, thus enhancing the SIF potential for inferring photosynthesis.

Miao, Guofang↗