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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Multi-omics data resource: Data package 24 (Pck024)

The data package consists of isolated pancreatic islets from 3 human donors treated with IL-1β, IFNγ or IL-1β + IFNγ for 6 h and IL-1β, IFNγ, IL-1β + IFNγ, IL-1β + IFNγ + NMMA or NMMA for 18 h and submitted for scRNA-seq. This study examines cytokine-stimulated changes in gene expression in human islets using single-cell RNA sequencing. Data contributors: Jennifer S Stancill & John A Corbett: Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA Data repository: GSE251730 Publication: 10.1093/function/zqae015

Sarkar, Soumyadeep [Pacific Northwest National Lab↗
DOE OSTI2018

National Solar Radiation Database (NSRDB)

The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2023. The NSRDB is updated annually and provides foundational information to support U.S. Department of Energy programs, research, industry and the general public. The NSRDB provides time-series data at 30-minute resolution of resource averaged over surface cells of 0.038 degrees in both latitude and longitude, or nominally 4 km in size. Additionally time series data at 5 minutes for the US and 10 minutes for North, Central and South America at 2 km resolution are produced from the next generation of GOES satellites and made available from 2019. The solar radiation values represent the resource available to solar energy systems. The data was created using cloud properties which are generated using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms developed by the University of Wisconsin. Fast all-sky radiation model for solar applications (FARMS) in conjunction with the cloud properties, and aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary source are used to estimate solar irradiance (GHI, DNI, and DHI). The Global Horizontal Irradiance (GHI) is computed for clear skies using the REST2 model. For cloud scenes identified by the cloud mask, FARMS is used to compute GHI and FARMS DNI is used to compute the Direct Normal Irradiance (DNI). The PATMOS-X model uses radiance images in visible and infrared channels from the Geostationary Operational Environmental Satellite (GOES) series of geostationary weather satellites. Ancillary variables needed to run REST2 and FARMS (e.g., aerosol optical depth, precipitable water vapor, and albedo) are derived from NASA's Modern Era-Retrospective Analysis (MERRA-2) dataset. Temperature and wind speed data are also derived from MERRA-2 and provided for use in NREL's System Advisor Model (SAM) to compute PV generation.

aerosol↗
DOE OSTI2015

Fall Prevention in Community Settings: Results from Implementing Stepping On in Three States

Stepping On is a community-based intervention that has been shown in a randomized controlled trial to reduce fall risk. The Wisconsin Institute for Healthy Aging adapted Stepping On for use in the United States and developed a training infrastructure to enable dissemination. The purpose of this study is to: (1) describe the personal characteristics of Stepping On participants; (2) quantify participants’ functional and self-reported health status at enrollment, and (3) measure changes in participants’ functional and self-reported health status after completing the program. Both survey and observed functional status [timed up and go (TUG) test] data were collected between September 2011 and December 2013 for 366 participants enrolled in 32 Stepping On programs delivered in Colorado, New York, and Oregon. Paired t-tests and general estimating equations models adjusted for socio-demographic factors were performed to assess changes over the program period. Among the 266 participants with pre–post survey data, the average participant age was 78.7 (SD ± 8.0) years. Most participants were female (83.4%), white (96.9%), and in good health (49.4%). The TUG test scores decreased significantly (p < 0.001) for all 254 participants with pre–post data. The change was most noticeable among high risk participants where TUG time decreased from 17.6 to 14.4 s. The adjusted odds ratio of feeling confident about keeping from falling was more than three times greater after completing Stepping On. Further, the adjusted odds ratios of reporting “no difficulty” for getting out of a straight back chair increased by 89%. Intended for older adults who have fallen in the past or are afraid of falling, Stepping On has the potential to reduce the frequency and burden of older adult falls.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

THE IONIZATION STRUCTURE OF SHARPLESS 2-264: MULTIWAVELENGTH OBSERVATIONS OF THE λ Ori H II REGION

We present velocity-resolved maps taken with the Wisconsin H-Alpha Mapper (WHAM) in Hα, [S ii] λ6716, and [N ii] λ6583 around the well-known O8 III star λ Ori A (HD 36861) (ℓ=185{sup ∘} to 205{sup ∘},b=−24{sup ∘} to −1{sup ∘}). The integrated intensity (v{sub LSR}=−80 to +80 km s{sup −1}), I{sub Hα}, within WHAM’s one-degree beams varies from ∼190 R near the center to ∼10 R on the periphery of the nebula where it becomes comparable to foreground and/or background emission in this complex region. Intensity ratios for [N ii]/Hα and [S ii]/Hα average 0.28 and 0.35, respectively. In both ratios, higher values are found preferentially at larger radii from λ Ori, although the behavior of [N ii]/Hα is complicated near the edges of the nebula. The [S ii]/[N ii] intensity ratio ranges from ∼0.5 to ∼1.0, with the value increasing toward larger radii (and lower Hα intensities). Variations of the [S ii]/Hα, [N ii]/Hα, and [S ii]/[N ii] line ratios in this diffuse region show some similar trends to those seen in the warm ionized medium (WIM) but with generally lower metal-line ratios. As with the WIM, the trends are driven by changes in the underlying physical parameters, most notably the ionization states and gas temperature. To investigate which cause might be dominant in this region, we use these extremely high signal-to-noise observations to construct a map of temperature and non-thermal velocity throughout the nebula. Using the line widths of Hα and [S ii], we separate thermal and non-thermal components and find spatial trends of these parameters within the nebula. Ion temperatures range between 4000 and 8000 K throughout the nebula. The non-thermal velocity map reveals a decrease in velocity from about 10 to 5 km s{sup −1} from the center to the edge of the lower half of the H ii region. In addition to using the widths as a measure of temperature, we also use the variation in [N ii]/Hα to estimate electron temperature. The results obtained from this diffuse H ii region around λ Ori can be compared to studies of the WIM to provide important insight into the nature of the diffuse ionized gas throughout the disk and halo of the Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

CHEMICAL ABUNDANCES IN NGC 5024 (M53): A MOSTLY FIRST GENERATION GLOBULAR CLUSTER

We present the Fe, Ca, Ti, Ni, Ba, Na, and O abundances for a sample of 53 red giant branch stars in the globular cluster (GC) NGC 5024 (M53). The abundances were measured from high signal-to-noise medium resolution spectra collected with the Hydra multi-object spectrograph on the Wisconsin–Indiana–Yale–NOAO 3.5 m telescope. M53 is of interest because previous studies based on the morphology of the cluster’s horizontal branch suggested that it might be composed primarily of first generation (FG) stars and differ from the majority of other GCs with multiple populations, which have been found to be dominated by the second generation (SG) stars. Our sample has an average [Fe/H] = −2.07 with a standard deviation of 0.07 dex. This value is consistent with previously published results. The alpha-element abundances in our sample are also consistent with the trends seen in Milky Way halo stars at similar metallicities, with enhanced [Ca/Fe] and [Ti/Fe] relative to solar. We find that the Na–O anti-correlation in M53 is not as extended as other GCs with similar masses and metallicities. The ratio of SG to the total number of stars in our sample is approximately 0.27 and the SG generation is more centrally concentrated. These findings further support that M53 might be a mostly FG cluster and could give further insight into how GCs formed the light element abundance patterns we observe in them today.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Warm Ionized Medium throughout the Sagittarius–Carina Arm

Wisconsin H-Alpha Mapper observations of Hα and [S ii] λ6716 emission are used to trace the vertical distribution and physical conditions of the warm ionized medium along the Sagittarius–Carina arm. CO emission, tracing cold molecular gas in the plane of the Galaxy, is used as a guide to isolate Hα and [S ii] λ6716 emission along individual spiral arms. Exponential scale heights of electron density squared (or emission measure) are determined using Hα emission above (below) the midplane to be 330±80 pc (550±230 pc) along the near Sagittarius arm, 300±100 pc (250±30 pc) along the near Carina arm, and >1000 pc along the far Carina arm. The emission measure scale height tends to increase as a function of Galactocentric radius along the Sagittarius–Carina arm for R{sub G}>8 kpc. Physical conditions of the ionized gas are analyzed using the [S ii]/Hα line ratio, which more closely traces I {sub Hα} than height above the plane, z, suggesting a stronger relationship with the in situ electron density. We interpret this result as further evidence for the majority of the observed diffuse emission originating from in situ ionized gas as opposed to scattered light from classical H ii regions in the plane.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A High Spectral Resolution Study of the Soft X-Ray Background with the X-Ray Quantum Calorimeter

We present here a combined analysis of four high spectral resolution observations of the Diffuse X-ray Background, made using the University of Wisconsin-Madison/Goddard Space Flight Center X-ray Quantum Calorimeter sounding rocket payload. The observed spectra support the existence of a ~0.1 keV Local Hot Bubble and a ~0.2 keV Hot Halo, with discrepancies between repeated observations compatible with expected contributions of time-variable emission from Solar Wind Charge Exchange. An additional component of ~0.9 keV emission observed only at low galactic latitudes can be consistently explained by unresolved dwarf M stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Data from: Associative nitrogen fixation (ANF) in switchgrass (Panicum virgatum) across a nitrogen input gradient

Associative N fixation (ANF), the process by which dinitrogen gas is converted to ammonia by bacteria in casual association with plants, has not been well-studied in temperate ecosystems. We examined the ANF potential of switchgrass (Panicum virgatum L.), a North American prairie grass whose productivity is often unresponsive to N fertilizer addition, via separate short-term 15N2 incubations of rhizosphere soils and excised roots four times during the growing season. Measurements occurred along N fertilization gradients at two sites with contrasting soil fertility (Wisconsin, USA Mollisols and Michigan, USA Alfisols). In general, we found that ANF potentials declined with long-term N addition, corresponding with increased soil N availability. Although we hypothesized that ANF potential would track plant N demand through the growing season, the highest root fixation rates occurred after plants senesced, suggesting that root diazotrophs exploit carbon (C) released during senescence, as C is translocated from aboveground tissues to roots for wintertime storage. Measured ANF potentials, coupled with mass balance calculations, suggest that ANF appears to be an important source of N to unfertilized switchgrass, and, by extension, to temperate grasslands in general.

09 BIOMASS FUELS↗
DOE OSTI2019

Data from: Nitrous oxide emissions during establishment of eight alternative cellulosic bioenergy cropping systems in the North Central United States

Greenhouse gas (GHG) emissions from soils are a key sustainability metric of cropping systems. During crop establishment, disruptive land-use change is known to be a critical, but under reported period, for determining GHG emissions. We measured soil N2O emissions and potential environmental drivers of these fluxes from a three-year establishment-phase bioenergy cropping systems experiment replicated in southcentral Wisconsin (ARL) and southwestern Michigan (KBS). Cropping systems treatments were annual monocultures (continuous corn, corn–soybean–canola rotation), perennial monocultures (switchgrass, miscanthus, and poplar), and perennial polycultures (native grass mixture, early successional community, and restored prairie) all grown using best management practices specific to the system. Cumulative three-year N2O emissions from annuals were 142% higher than from perennials, with fertilized perennials 190% higher than unfertilized perennials. Emissions ranged from 3.1 to 19.1 kg N2O-N ha−1 yr−1 for the annuals with continuous corn > corn–soybean–canola rotation and 1.1 to 6.3 kg N2O-N ha−1 yr−1 for perennials. Nitrous oxide peak fluxes typically were associated with precipitation events that closely followed fertilization. Bayesian modeling of N2O fluxes based on measured environmental factors explained 33% of variability across all systems. Models trained on single systems performed well in most monocultures (e.g., R2 = 0.52 for poplar) but notably worse in polycultures (e.g., R2 = 0.17 for early successional, R2 = 0.06 for restored prairie), indicating that simulation models that include N2O emissions should be parameterized specific to particular plant communities. Our results indicate that perennial bioenergy crops in their establishment phase emit less N2O than annual crops, especially when not fertilized. These findings should be considered further alongside yield and other metrics contributing to important ecosystem services.

09 BIOMASS FUELS↗
DOE OSTI2018

Data from: Harvesting biofuel grasslands has mixed effects on natural enemy communities and no effects on biocontrol services

1.Perennial bioenergy systems, such as switchgrass and restored prairies, are alternatives to commonly used annual monocultures such as maize. Perennial systems require lower chemical input, provide greater ecosystem services such as carbon storage, greenhouse gas mitigation, and support greater biodiversity of beneficial insects. However, biomass harvest will be necessary in managing these perennial systems for bioenergy production, and it is unclear how repeated harvesting might affect ecosystem services. 2.In this study, we examined how repeated production-scale harvesting of diverse perennial grasslands influences vegetation structure, natural enemy communities (arthropod predators and parasitoids), and natural biocontrol services in two states (Wisconsin and Michigan, USA) over multiple years. 3.We found that repeated biomass harvest reduced litter biomass and increased bare ground cover. Some natural enemy groups, such as ground-dwelling arthropods, decreased in abundance with harvest whereas others, such as foliar-dwelling arthropods increased in abundance. The disparity in responses is likely due to how different taxonomic groups utilize vegetation and differences in dispersal abilities. 4.At the community level, biomass harvest altered community composition, increased total arthropod abundance, and decreased evenness but did not influence species richness, diversity, or biocontrol services. Harvest effects varied with time, diminishing in strength both within the season (for total abundance and evenness), across seasons (for evenness), or were consistent throughout the duration of the study (for community composition). Greater functional redundancy and compensatory responses of the different taxonomic groups may have buffered against the potentially negative effects of harvest on biocontrol services. 5.Synthesis and applications. Our results show that in the short-term, repeated harvesting of perennial grasslands (when insect activity is low) consistently altered vegetation structure but had mixed effects on natural enemy communities and no discernable effects on biocontrol services. However, the long-term effects of repeated harvesting on vegetation structure, natural enemies, and other arthropod-derived ecosystem services such as pollination and decomposition remain largely unknown.

09 BIOMASS FUELS↗
DOE OSTI2024

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Meteorology & Atmospheric Sciences↗
DOE OSTI2018

Identifying Sociomarkers of Pediatric Asthma Patients at Risk of Hospital Revisiting

ObjectiveAsthma is one of the most common chronic childhood diseases in the United States [2, 3]. In addition to its pervasiveness, pediatric asthma shows high sensitivity to the environment. Combining medical-social dataset with machine learning methods we demonstrate how socio-markers play an important role in identifying patients at risk of hospital revisits due to pediatric asthma within a year.IntroductionA socio-marker is a measurable indicator of social conditions where a patient is embedded in and exposed to, being analogous with a biomarker indicating the severity or presence of some disease state. Social factors are one of the most clinical health determinants [1], which play a critical role in explaining health outcomes. Socio-markers can help medical practitioners and researchers to reliably identify high-risk individuals in a timely manner.MethodsWe collected data from three different sources: pediatric asthma encounter records from Jan 1st, 2016 to Dec 31st, 2016 at a children’s hospital, the 2010 U.S census data and neighborhood quality survey data by Memphis Property Hub. After merging these datasets we examine the effect of social features in identifying the patients who visited the hospital more than once during the observation period. We only use the first time visit (3,678 cases) to avoid over-counting of the same patients. In addition to demographic features (age, gender, insurance type, and race (African American and White)), we incorporate the social features such as the proportion of individuals living below the federal poverty level, blight prevalence, neighborhood quality, neighborhood quality inequality, trash dumping presence, the broken window pervasiveness within the zip code area of patients’ residence are included.We then implemented a Support Vector Machine (SVM) based classification model using abovementioned 11 social features. The classification outcome is either patient visits the hospital only one-time (class 0) or revisits the hospital within a year (class 1). Among 3,678 unique patients in the dataset, only 823 pediatric patients revisited hospital with asthma. So, to overcome the class imbalance issue, we have used 823 patients’ data (randomly selected in 1,000 iterations) from each class. Further, to avoid overfitting and ensure generalizability, we divided the dataset as training, test, and validation with a proportion of 60%, 20%, and 20%, respectively. The reported test (5-folds cross-validation using training and testing data) and validation accuracy of the SVM method are averaged over 1,000 iterations to avoid sampling error and bias.ResultsThe proposed socio-marker model resulted in an average classification accuracy of 63.70% for the test set and 63.67 % for the validation set. Further, the average specificity (the total true negative cases divided by the sum of true negative and false positive) and sensitivity (the total number of true positive cases divided by the sum of positive predicted cases) is found to be 62.79% and 64.77%, respectively for the test set and 62.79% and 64.83%, respectively for the validation set. Results of this study suggest that socio-marker features that are not directly related to a patient’s medical conditions can still predict whether the patient will come back to the hospital within a year or not with approximately 64% accuracy.ConclusionsBringing the socio-marker features in the surveillance system may ease the burden of detecting the patients at risk of revisiting the hospital. The results should be interpreted with caution because we only used 12-month period of observation and the visit beyond the observation window is not considered. Also the patients may have visited different hospitals which are not captured in the data.References1. Booske BC, Athens JK, Kindig DA, Park H, Remington PL: Different perspectives for assigning weights to determinants of health. University of Wisconsin: Population Health Institute 2010.2. Subbarao P, Mandhane PJ, Sears MR: Asthma: epidemiology, etiology and risk factors. Canadian Medical Association Journal 2009, 181(9):E181-E190.3. Gold DR, Wright R: Population disparities in asthma. Annu Rev Public Health 2005, 26:89-113.

Shin, Eun Kyong↗
DOE OSTI2016

CHARMS Combined Data Set

These multi-wavelength lidar data were collected during the Combined HSRL and Raman lidar Measurement Study (CHARMS) IOP that occurred during July through September 2015 at SGP. During CHARMS the University of Wisconsin HSRL was located at SGP and acquired aerosol backscatter profiles at 532 nm and 1064 nm and aerosol backscatter, extinction, and depolarization profiles at 532 nm. The HSRL aerosol profiles, when combined with the aerosol backscatter and extinction profiles (355 nm) collected by the SGP Raman lidar, provide a suite of three aerosol backscatter (355, 532, 1064 nm) and two aerosol extinction (355, 532 nm) profiles for use in advanced aerosol microphysical retrievals. The data files in this PI product contain this suite of aerosol backscatter (355, 532, 1064), extinction (355, 532 nm), and depolarization (532 nm) profiles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER SPARC AERI Data

These files contain 24 hour periods of retrieved thermodynamic profiles derived from observations collected by the University of Wisconsin–Madison Space Science and Engineering Center Portable Atmospheric Research Center (SPARC) Atmospheric Emitted Radiance Interferometer (AERI). The TROPoe algorithm is a python equivalent to the AERIoe algorithm (see Turner and Loehnert, 2014; Turner and Blumberg 2019). These data were collected during the TRACER project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

bioreactor sludge metagenome

Anaerobic fermentation bioreactor microbial communities from Madison, Wisconsin, United States. The goal of this study is to characterize a central set of genes relevant to medium chain fatty acid (MCFA) production to guide screens of putative MCFA-producing microorganisms from additional environments or grown on different substrates.

butyric↗