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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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Volume VII presents the chemical benchmarks for sediment: marine. Consult Volume I for information on the sources.
Volume VI presents the chemical benchmarks for sediment: fresh water. Consult Volume I for information on the sources.
Volume V presents the chemical benchmarks for surface water: general. The benchmarks here are applicable to both fresh water and marine or where no differentiation was made by the source. These values are not repeated in the fresh water and marine categories. Likewise, values listed in the fresh water and marine categories are not repeated in the generic categories. Consult Volume I for information on the sources.
Volume IV presents the chemical benchmarks for surface water: marine. Consult Volume I for information on the sources.
Volume III presents the chemical benchmarks for surface water: Fresh water. Consult Volume I for information on the sources.
Volume II presents the chemical benchmarks for soil. Consult Volume I for information on the sources.
Current HVAC systems can constitute as much as half of a building’s total energy consumption, depending on its use. More specifically cooling, particularly in hotter climates or for energy intensive applications, like data centers, can comprise between 10-30% of the total energy use. These cooling systems are largely comprised of compressor-based direct expansion systems and chilled water systems that use refrigerants or water, respectively, to reject heat. . Electrocaloric (EC) cycles present an eco-friendly alternative to these conventional processes.
Machine learning (ML) is a powerful tool for functional material design. In this work, we combine first-principles density function theory with ML to develop perovskite database and design O<sub>2</sub> sensors for harsh environmental applications.
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Explore the source record for details and available documents.
Presentation for Reliability and Maintainability Symposium in January 2026. This is a ROUGH DRAFT that will be blind peer reviewed.
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This dataset contains binary carbon-source growth results for bacterial isolates associated with Populus roots. The isolates are part of the Populus culture collection described by Carper et al. (2021), Cultivating the Bacterial Microbiota of Populus Roots (https://doi.org/10.1128/msystems.01306-20).
The popularity of ready-to-eat (RTE) salads has prompted novel technology to prolong the shelf life of their ingredients. Fresh-cut romaine lettuce is widely used in RTE salads; however, its tendency to quickly discolor continues to be a challenge for the industry. Selecting the ideal lettuce accessions for use in RTE salads is essential to ensure maximum shelf life, and it is critical to have a practical way to assess and compare the quality of multiple lettuce accessions that are being considered for use in fresh-cut applications. Thus, in this work we aimed to determine whether a computer vision system (CVS) composed of image acquisition, processing, and analysis could be effective to detect visual quality differences among 16 accessions of fresh-cut romaine lettuce during postharvest storage. The CVS involved a post-capturing color correction, effective image segmentation, and calculation of a browning index, which was tested as a predictor of quality and shelf life of fresh-cut romaine lettuce. The results demonstrated that machine vision software can be implemented to replace or supplement the scoring of a trained panel and instrumental quality measurements. Overall visual quality, a key sensory parameter that determines food preferences and consumer behavior, was highly correlated with the browning index, with a Pearson correlation coefficient of −0.85. Other important sensory decision parameters were also strongly or moderately correlated with the browning index, with Pearson correlation coefficients of −0.84 for freshness, 0.79 for off odor, and 0.57 for browning. The ranking of the accessions according to quality acceptability from the sensory evaluation produced a similar pattern to those obtained with the CVS. This study revealed that multiple lettuce accessions can be effectively benchmarked for their performance as fresh-cut sources via a CVS-based method. Future opportunities and challenges in using machine vision image processing to predict consumer preferences for RTE salad greens is also discussed.
Fresh-cut romaine lettuce’s high perishability challenges ready-to-eat (RTE) salad production. Selecting cultivars less prone to browning and decay is crucial for extending shelf life. Traditional quality evaluation methods using instrumentation and trained panelists are time-consuming and logistically complex. This study investigated the effectiveness of untrained volunteers in assessing fresh-cut romaine lettuce quality. Given that the average consumer in the USA is familiar with the flavor characteristics of romaine lettuce, this study proposed to investigate the value of having untrained volunteers discern the quality of fresh-cut romaine lettuce. Therefore, six romaine lettuce accessions (Green Forest, King Henry, Parris Island Cos, PI 491224, SM13-R2, and Sun Valley) were assessed for sensory quality attributes (browning, green color, decay, and overall quality) and compared with instrumentation analyses (gas composition including O2 and CO2, electrolyte leakage, and color). The results showed significant quality differences (p < 0.05) among the accessions, with some seasonal variability. Very importantly, the consumers’ (n = 159) assessments revealed similar results to those produced by either instrumentation or a trained panel. The consumers provided sensory scores that allowed for the grouping of accessions based on their postharvest quality, which efficiently matched their pedigree relationship. In conclusion, ad hoc consumer panels can be an effective way to characterize the quality of romaine lettuce for RTE salads.
Background: Vaccine development against Chlamydia, a prevalent sexually transmied infection (STI), is imperative due to its global public health impact. However, significant challenges arise in the production of effective subunit vaccines based on recombinant protein antigens, particularly with membrane proteins like the Major Outer Membrane Protein (MOMP). Methods: Cellfree protein synthesis (CFPS) technology is an aractive approach to address these challenges as a method of high-throughput membrane protein and protein complex production coupled with nanolipoprotein particles (NLPs). NLPs provide a supporting scaffold while allowing easy adjuvant addition during formulation. Over the last decade, we have been working toward the production and characterization of MOMP-NLP complexes for vaccine testing. Results: The work presented here highlights the expression and biophysical analyses, including transmission electron microscopy (TEM) and dynamic light scaering (DLS), which confirm the formation and functionality of MOMP-NLP complexes for use in animal studies. Moreover, immunization studies in preclinical models compare the past and present protective efficacy of MOMP-NLP formulations, particularly when co-adjuvanted with CpG and FSL1. Conclusion: Ex vivo assessments further highlight the immunomodulatory effects of MOMP-NLP vaccinations, emphasizing their potential to elicitrobust immune responses. However, further research is warranted to optimize vaccine formulations further, validate efficacy against Chlamydia trachomatis, and beer understand the underlying mechanisms of immune response.
This study is using a health systems approach to investigate low-value care (LVC) may provide insights into structural drivers of this pervasive problem.
Poster for American Physical Society (APS) March Meeting.