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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests

Female reproductive disorders (FRDs) are common health conditions that may present with significant symptoms. Diet and environment are potential areas for FRD interventions. We utilized a knowledge graph (KG) method to predict factors associated with common FRDs (for example, endometriosis, ovarian cyst, and uterine fibroids). We harmonized survey data from the Personalized Environment and Genes Study (PEGS) on internal and external environmental exposures and health conditions with biomedical ontology content. We merged the harmonized data and ontologies with supplemental nutrient and agricultural chemical data to create a KG. We analyzed the KG by embedding edges and applying a random forest for edge prediction to identify variables potentially associated with FRDs. We also conducted logistic regression analysis for comparison. Across 9765 PEGS respondents, the KG analysis resulted in 8535 significant or suggestive predicted links between FRDs and chemicals, phenotypes, and diseases. Amongst these links, 32 were exact matches when compared with the logistic regression results, including comorbidities, medications, foods, and occupational exposures. Mechanistic underpinnings of predicted links documented in the literature may support some of our findings. Our KG methods are useful for predicting possible associations in large, survey-based datasets with added information on directionality and magnitude of effect from logistic regression. These results should not be construed as causal but can support hypothesis generation. This investigation enabled the generation of hypotheses on a variety of potential links between FRDs and exposures. Future investigations should prospectively evaluate the variables hypothesized to impact FRDs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Maximizing MWh: A statistical analysis of the performance of utility-scale photovoltaic projects in the United States

Despite significant cost declines utility-scale solar projects have to perform well over their lifetime in order to return profits in a low-PPA environment of under $50/MWh. Using multivariate regression analysis this paper examines the 2014 Net Capacity Factors for 128 utility-scale projects that came online before the end of 2013 and explores the impact (in decreasing order of importance) of global horizontal irradiance, tracking technology, inverter loading ratios and project vintage plus three other interactive variables on performance. The model complies with the assumptions of OLS regressions and explains 93% of the observed NCF variation.

Bolinger, M↗
NASA NTRS1977

Quantitative analysis of aircraft multispectral-scanner data and mapping of water-quality parameters in the James River in Virginia

Statistical analysis techniques were applied to develop quantitative relationships between in situ river measurements and the remotely sensed data that were obtained over the James River in Virginia on 28 May 1974. The remotely sensed data were collected with a multispectral scanner and with photographs taken from an aircraft platform. Concentration differences among water quality parameters such as suspended sediment, chlorophyll a, and nutrients indicated significant spectral variations. Calibrated equations from the multiple regression analysis were used to develop maps that indicated the quantitative distributions of water quality parameters and the dispersion characteristics of a pollutant plume entering the turbid river system. Results from further analyses that use only three preselected multispectral scanner bands of data indicated that regression coefficients and standard errors of estimate were not appreciably degraded compared with results from the 10-band analysis.

Johnson, R. W.↗
NASA NTRS1985

Measurements of CCl3F, CCl2F2, CCl4, N2O and SF6 in the Northern Hemisphere stratosphere

An overview of the Department of Energy's High Altitude Sampling Program and some recent trace gas measurement results are presented. Analysis of whole air samples, collected in pressurized bottles, provides information on stratospheric inventories and distributions for CCl3F, CCl2F2, CCl4, N2O and SF6 in the Northern Hemisphere. Based on a linear regression analysis of the data the estimated mean Northern Hemisphere stratospheric concentration of each gas increased as follows: CCl3F changed from 54 to 142 p1/1 (4/74-11/83); CCl2F2 changed from 133 to 268 p1/1 (4/76-11/83); SF6 changed from 160 to 480 f1/1 (4/74-11/83); CC1, changed from 58 to 91 p1/1 (4/75-11/83); N2O changed from 246 to 261 n1/1 (4/76-11/83). The calculated mean Northern Hemisphere stratospheric concentrations of N2O, CCl3F, CCl2F2, and CCl4 after 1980 show larger than expected fluctuations with time. Recent volcanic activity may be a partial cause for these fluctuations through induced changes in stratospheric dynamical processes.

Leifer, R.↗
NASA NTRS1994

Depletions in winter total ozone values over southern England

A study has been made of the recently re-evaluated time series of daily total ozone values for the period 1979 to 1992 for southern England. The series consists of measurements made at two stations, Bracknell and Camborne. The series shows a steady decline in ozone values in the spring months over the period, and this is consistent with data from an earlier decade that has been published but not re-evaluated. Of exceptional note is the monthly mean for January 1992 which was very significantly reduced from the normal value, and was the lowest so far measured for this month. This winter was also noteworthy for a prolonged period during which a blocking anticyclone dominated the region, and the possibility existed that this was related to the ozone anomaly. It was possible to determine whether the origin of the low ozone value lay in ascending stratospheric motions. A linear regression analysis of ozone value deviation against 100hPa temperature deviations was used to reduce ozone values to those expected in the absence of high pressure. The assumption was made that the normal regression relation was not affected by atmospheric anomalies during the winter. This showed that vertical motions in the stratosphere only accounted for part of the ozone anomaly and that the main cause of the ozone deficit lay either in a reduced stratospheric circulation to which the anticyclone may be related or in chemical effects in the reduced stratospheric temperatures above the high pressure area. A study of the ozone time series adjusted to remove variations correlated with meteorological quantities, showed that during the period since 1979, one other winter, that of 1982/3, showed a similar although less well defined deficit in total ozone values.

Lapworth, A.↗
NASA NTRS1977

Application of LANDSAT system for improving methodology for inventory and classification of wetlands

The author has identified the following significant results. LANDSAT and aircraft data were compared for differences in absolute numbers of water bodies in the two data sets. This comparison was done using a linear regression analysis. The coefficients of determination were 0.65 and 0.74 for data of May and July, respectively. Standard statistical procedures were used to adjust the LANDSAT pond counts to actual pond numbers based on regression relationships.

Gilmer, D. S.↗
NASA NTRS1973

Analysis of remotely sensed data for detecting soil limitations

During 1971 and 1972 a detailed study was conducted on a fallow field in the proposed Oahe Irrigation Project to determine the relationship between the tonal variation observed on aerial photographs and the properties of eroded soil. Correlation and regression analysis of digitized, multiemulsion, color infrared film (2443) data and detailed field data revealed a highly significant correlation between film transmittance and several soil properties indicative of the erosion limitation. Computer classification of the multiemulsion film data resulted in maps portraying the eroded soil and the normal soil. Both correlation and computer classification results were best using the reflectance data from the red spectral band. The results showed film transmittance was actually measuring the reflectivity of the soil surface which was increased by the incorporation of the light colored, calcareous parent material exposed by erosion or tillage on soils with thin surface horizons.

Benson, L. A.↗
DOE OSTI2022

Development of a prediction model for radiotherapy response among patients with head and neck squamous cell carcinoma based on the tumor immune microenvironment and hypoxia signature

Abstract Introduction The immune system and hypoxia are major factors influencing radiosensitivity in patients with different cancer types. This study aimed at developing a model to predict radiotherapy response in patients with head and neck squamous cell carcinoma (HNSCC) based on the tumor immune microenvironment and hypoxia signature. Materials and Methods We first evaluated the hypoxia status and tumor immune microenvironment in the Cancer Genome Atlas (TCGA) cohort by using transcriptomic data. Differentially expressed genes (DEGs) were identified between the “high immunity and low hypoxia” and “low immunity and high hypoxia” groups and those DEGs significantly associated with disease‐specific survival in the univariate Cox regression analysis were selected as the prognostic DEGs. We selected the immune hypoxia–related genes (IHRGs) by intersecting prognostic DEGs with immune and hypoxia gene sets. We used the IHRGs to train a multivariate Cox regression model in the TCGA cohort, based on which we calculated the IHRG prognostic index (IHRGPI) for each patient and validated its efficacy in predicting radiotherapy response in the Gene Expression Omnibus cohorts. Furthermore, we explored potential mechanisms and effective combinational treatment strategies for different IHRGPI groups. Results Five IHRGs were used to construct the IHRGPI, which was used to dichotomize the cohorts. The patients with lower IHRGPI showed a better radiotherapy response across different cohorts and endpoints, including overall survival, progression‐free survival, and recurrence‐free survival ( p < 0.05). Patients with higher IHRGPI showed greater hypoxia and lesser immune cell infiltration. A lower IHRGPI indicated a better immunotherapy response, while a higher IHRGPI indicated a better chemotherapy response. Conclusions IHRGPI is promising for predicting radiotherapy response and guiding combinational treatment strategies in patients with HNSCC.

Zhu, Guang‐Li↗
NASA NTRS1978

Red and photographic infrared linear combinations for monitoring vegetation

In situ collected spectrometer data were used to evaluate and quantify the relationships between various linear combinations of red and photographic infrared radiances and experimental plot biomass, leaf water content, and chlorophyll content. The radiance variables evaluated included the red and photographic infrared (IR) radiance and the linear combinations of the IR/red ratio, the square root of th IR/red difference, the vegetation index, and the transformed vegetation index. In addition, the corresponding green and red linear combinations were evaluated for comparative purposes. Three data sets were used from June, September, and October sampling periods. Regression analysis showed the increase utility of the IR and red linear combinations vis-a-vis the same green and red linear combinations. The red and IR linear combinations had 7% and 14% greater regression significance than the green and red linear combinations for the June and September sampling periods, respectively. The VI, TVI, and square root of the IR/red ration were the most significant followed closely by the IR/red ratio. Less than 6% difference separated the highest and lowest of these four IR and red linear combinations. The use of these linear combinations was shown to be sensitive primarily to the green leaf area or green leaf biomass.

Tucker, C. J.↗
NASA NTRS2018

Reliability of the Danish Aerospace Corporation Portable Pulmonary Function System

Metabolic gas analysis is a critical component of investigations that measure cardio-pulmonary exercise responses during and after long-duration spaceflight. The primary purpose of the current study was to determine the reliability and intra-subject repeatability of a metabolic gas analysis device, the Portable Pulmonary Function System (PPFS), designed for use on the International Space Station (ISS). The second objective of this study was to directly compare PPFS measurements of expired oxygen and carbon dioxide (FEO2 and FECO2) to values obtained from a well-validated clinical metabolic gas analysis system (ParvoMedics TrueOne (c) [PM]). Eight subjects performed four peak cycle tests to maximal exertion. The first test was used to prescribe work rates for the subsequent test sessions. Metabolic gas analysis for this test was performed by the PM, but samples of FEO2 and FECO2 also were simultaneously collected for analysis by the PPFS. Subjects then performed three additional peak cycle tests, consisting of three 5-min stages designed to elicit 25%, 50%, and 75% maximal oxygen consumption (VO2max) followed by stepwise increases of 25 W/min until subjects reached volitional exhaustion. Metabolic gas analysis was performed using the PPFS for these tests. Intraclass correlation coefficients (ICC), within-subject standard deviations (WS SD), and coefficients of variation (CV%) were calculated for the repeated exercise tests. Mixed model regression analysis was used to compare paired FEO2 and FECO2 values obtained from the PPFS and the PM during the initial test. The ICC values for oxygen consumption (VO2), carbon dioxide production (VCO2), and ventilation (VE) indicate that the PPFS is highly reliable (0.79 to 0.99) for all exercise levels tested; however, ICCs for respiratory exchange ratio (RER) were low ( 0.11 - 0.51), indicating poor agreement between trials during submaximal and maximal exercise. Overall, CVs ranged from 1.6% to 6.7% for all measurements, a finding consistent with reported values that were obtained using other metabolic gas analysis techniques. The PPFS and PM produced comparable FEO2 data; however, there was less agreement between measures of FECO2 obtained from the two devices, particularly at lower CO2 concentrations. The PPFS appears, in practically all respects, to yield highly reliable metabolic gas analysis data. Lower reliability of RER measurements reported in the literature and likely is not a function of the PPFS device. Further examination of PPFS CO2 data is warranted to better understand the limitations of these PPFS measurements. Overall, the PPFS when used for repeated measures of cardio-pulmonary exercise should provide accurate and reliable data for studies of human adaptation to spaceflight.

Portable Pulmonary Function System (PPFS)↗
DOE OSTI2023

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2025

Jemez Pueblo Agriculture: Monitoring Rangeland Conditions to Inform Drought and Land Management in New Mexico

The Jemez Pueblo, a community located in the semi-arid high desert region of northcentral New Mexico, faces challenges with drought mitigation and livestock management. NASA DEVELOP partnered with the Pueblo of Jemez Natural Resources Department and The Nature Conservancy to provide recent and historical rangeland conditions to aid present decision-making, which relies on cultural practices, site familiarity, available resources, and physical data. This partnership offers the opportunity to support management practices by leveraging remote sensing and virtual fencing technologies. Our project explored Rangeland Analysis Platform (RAP) products incorporating NASA Earth observation Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2 remote-sensed imagery as an agricultural land management tool. We performed linear regression analysis to evaluate RAP data to field data and explored RAP annual herbaceous biomass, ground cover trends, and climatic factors at the pasture level. We then computed study area summary statistics, performed pixel-by-pixel trend analysis across the study period, and evaluated ground cover trends near water sources. Based on available data, RAP was poorly correlated to bare ground and herbaceous biomass, generally underestimating the former and overestimating the latter. To improve the evaluation of RAP products, we suggest increasing the spatiotemporal distribution of the field dataset. According to RAP, from 1986 to 2023, the site became hotter and drier, bare ground increased, and annual forbs and grasses increased while perennials decreased. RAP products did not agree with field-collected data; however, the trends over time may be useful for informing rangeland management actions.

cattle grazing management↗
DOE OSTI2019

Prognostic value of left ventricular dyssynchrony evaluated by gated myocardial perfusion imaging in patients with chronic kidney disease and normal perfusion defect scores

Background: This study aimed to investigate whether indices of left ventricular (LV) dyssynchrony by gated myocardial perfusion SPECT (GMPS) could be useful to predict prognosis in chronic kidney disease (CKD) patients with normal perfusion defect scores. Methods: One hundred and sixty-seven CKD patients with normal perfusion defect scores on adenosine-stress {sup 201}Tl GMPS and no previous history of overt heart diseases were enrolled. Phase standard deviation (PSD) and bandwidth (BW) were automatically calculated from GMPS. The major adverse cardiac events (MACEs) for a mean of 560 days were defined as sudden cardiac death, fatal arrhythmias, and acute coronary syndrome requiring urgent coronary revascularization. Patients were divided into two groups according to the presence or absence of MACEs. Results: The MACEs occurred in 12 patients (7.1%). Patients who experienced MACEs showed significantly higher PSD and wider BW than those who did not. In the Kaplan-Meier event-free survival analysis, cardiac event rate was significantly higher in the high-PSD and wide-BW group (n = 81) than in the low-PSD and narrow-BW group (n = 71) (P = .002). The multivariate regression analysis revealed that the PSD was associated with MACEs (odds ratio 1.33, 95% confidence interval 1.05-1.69, P = .01). Conclusion: The LV dyssynchrony indices from GMPS may be novel prognostic predictors in CKD patients with normal perfusion defect scores.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Levelized Cost of Coating (LCOC) for selective absorber materials

A new metric has been developed to evaluate and compare selective absorber coatings for concentrating solar power applications. Previous metrics have typically considered the performance of the selective coating (i.e., solar absorptance and thermal emittance), but cost and durability were not considered. This report describes the development of the levelized cost of coating (LCOC), which is similar to the levelized cost of energy (LCOE) commonly used to evaluate alternative energy technologies. The LCOC is defined as the ratio of the annualized cost of the coating (and associated costs such as labor and number of heliostats required) to the average annual thermal energy produced by the receiver. The baseline LCOC using Pyromark 2500 paint was found to be %240.055/MWht, and the distribution of LCOC values relative to this baseline were determined in a probabilistic analysis to range from -%241.6/MWht to %247.3/MWht, accounting for the cost of additional (or fewer) heliostats required to yield the same baseline average annual thermal energy produced by the receiver. A stepwise multiple rank regression analysis showed that the initial solar absorptance was the most significant parameter impacting the LCOC, followed by thermal emittance, degradation rate, reapplication interval, and downtime during reapplication.

14 SOLAR ENERGY↗
NASA NTRS1988

Parametric analysis of synthetic aperture radar data for the study of forest stand characteristics

A parametric analysis of a Gulf Coast forest stand was performed using multipolarization, multipath airborne SAR data, and forest plot properties. Allometric equations were used to compute the biomass and basal area for the test plots. A multiple regression analysis with stepwise selection of independent variables was performed. It is found that forest stand characteristics such as biomass, basal area, and average tree height are correlated with SAR data.

Wu, Shih-Tseng↗
DOE OSTI2017

Prediction of spout diameter in gas-solid spouted beds using factorial design of experiments approach with the aid of advanced optical fibre probe

In this study, the effects of five operating and design variables (solid density, static bed height, particle diameter, superficial gas velocity, and inlet diameter) on the average spout diameter of a 0.152 m inside diameter gas-solid spouted bed have been assessed experimentally using advanced gas-solid optical fibre probe technique. Statistical analysis of the experimental data including the factorial design of the experiments using MINITAB17 statistical software has been performed to determine the extent of the effects of these variables on the spout diameter as a case study. It was found that all five operating and design variables, except the solid density together with the 2-ways interactions between particles size and inlet diameter, in addition to gas velocity and inlet diameter, have a significant effect on the average spout diameter. Regression analysis was performed to correlate these variables with the average spout diameter for the gas-solid spouted beds. The obtained preliminary regression correlation was able to closely predict the average spout diameter of this work with the mean relative deviation value of 0.7 %.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Comparison of Two Surface Contamination Sampling Techniques Conducted for the Characterization of Two Pajarito Site Manhattan Project National Historic Park Properties

Technical Area-18 (TA-18), also known as Pajarito Site, is located on Los Alamos National Laboratory property and has historic buildings that will be included in the Manhattan Project National Historic Park. Characterization studies of metal contamination were needed in two of the four buildings that are on the historic registry in this area, a “battleship” bunker building (TA-18-0002) and the Pond cabin (TA-18-0029). However, these two buildings have been exposed to the elements, are decades old, and have porous and rough surfaces (wood and concrete). Due to these conditions, it was questioned whether standard wipe sampling would be adequate to detect surface dust metal contamination in these buildings. Thus, micro-vacuum and surface wet wipe sampling techniques were performed side-by-side at both buildings and results were compared statistically. A two-tail paired t-test revealed that the micro-vacuum and wet wipe techniques were statistically different for both buildings. Further mathematical analysis revealed that the wet wipe technique picked up more metals from the surface than the microvacuum technique. Wet wipes revealed concentrations of beryllium and lead above internal housekeeping limits; however, using an yttrium normalization method with linear regression analysis between beryllium and yttrium revealed a correlation indicating that the beryllium levels were likely due to background and not operational contamination. PPE and administrative controls were implemented for National Park Service (NPS) and Department of Energy (DOE) tours as a result of this study. Overall, this study indicates that the micro-vacuum technique may not be an efficient technique to sample for metal dust contamination.

47 OTHER INSTRUMENTATION↗
NASA NTRS1978

Applications of modeling to analysis and processing of Landsat data

The Suits bidirectional reflectance model (1972) for vegetation canopies was used to calculate reflectance values for the four Landsat spectral bands under a variety of canopy and observation conditions. Relationships between characteristics of developing wheat fields and associated reflectances were studied. Coincident measurements of crop reflectance and Landsat signals were compared using regression analysis techniques. The model was also applied to forest situations both to help establish the extent to which Landsat may provide direct information about conditions occurring beneath forest overstories and to help develop methods for reducing the effects of terrain slope and aspect in the processing of Landsat data. Finally, a relationship based on model calculations was used to adjust Landsat signal values and was found to reduce topography-related variability and improve subsequent classification performance.

Malila, W. A.↗