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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Nutritional status and random blood glucose, cholesterol and triglyceride test among Malaysian Army (MA) personnel in Kuala Lumpur

With the rising trend of obesity among the general population, it is also important to assess the obesity and health status among military population. The aim of this study was to determine the prevalence of overweight and obesity among Malaysian Army (MA) personnel as well as the relationship between selected socio-demographics factors, antropometric profiles, body composition and random blood test value. A cross sectional study involving 378 male military personnel aged between 20 to 48 years old was conducted at two MA bases in Kuala Lumpur between November and December 2012. Antropometric measurements included height, weight and waist circumference (WC). Body fat percentage was measured using bioelectrical impedance analysis method (Tanita TBF-300A). Mean height, weight, BMI, WC, body fat percentage, age, monthly income and duration of service were 1.71 ± 0.6 m, 71.7 ± 12.2 kg, 24.6 ± 4.1 kg/m{sup 2}, 87.0 ± 10.0 cm, 23.4 ± 6.6%, 29.1 ± 5.5 years, RM 2115.12 ± 860.70 and 9.9 ± 5.6 years respectively. According to WHO (1998) classification of BMI, 3.2% of the subjects were underweight, 54.8% normal, 32.8% overweight and 9.3% obese. It was obeserved that 40.2% of the subjects had waist circumference value of 90 cm or more and were considered high risk for diebetes and cardiovascular diseases. This study found that BMI was highly correlated with weight (r=0.925, p<0.05), WC (r=0.852, p<0.05) and body fat percentage. Body fat percentage also show high correlation with weight (r=0.759, p<0.05) and WC (r=0.768, p<0.05. The result from 173 of 378 subjects that were selected for random blood test found that 4.6%, 3.5% and 26.0% had diabetes, high cholesterol and high triglyceride respectively. There was a weak correlation between random blood glucose level with weight (r=0.221, p<0.05), BMI (r=0.243, p<0.05), WC (r=0.298, p<0.05), body fat percentage (r=0.163, p<0.05) and age (r=0.223, p<0.05). Random blood cholesterol level had significant correlation with weight (r=0.284, p<0.05), BMI (r=0.260, p<0.05), WC (r=0.362, p<0.05) and body fat percentage (r=0.313, p<0.05). It was also noted that random blood triglyceride level was significantly correlated with weight (r=0.223, p<0.05), BMI (r=0.312, p<0.05), WC (r=0.288, p<0.05), body fat percentage (r=0.287, p<0.05) and age (r=0.268 p<0.05). These results call for attention to the existence of overweight and obesity as well as the risk of non-communicable diseases among military population. Therefore, future intervention from the aspect of nutritional education and health awareness can benefit thus optimizing the health status of MA military personnel.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Benchmark Dose Analysis of DNA Damage Biomarker Responses Provides Compound Potency and Adverse Outcome Pathway Information for the Topoisomerase II Inhibitor Class of Compounds

Genetic toxicology data have traditionally been utilized for hazard identification to provide a binary call for a compound's risk. Recent advances in the scientific field, especially with the development of high‐throughput methods to quantify DNA damage, have influenced a change of approach in genotoxicity assessment. The in vitro MultiFlow® DNA Damage Assay is one such method which multiplexes γH2AX, p53, phospho‐histone H3 biomarkers into a single‐flow cytometric analysis (Bryce et al., [2016]: Environ Mol Mutagen 57:546–558). This assay was used to study human TK6 cells exposed to each of eight topoisomerase II poisons for 4 and 24 hr. Using PROAST v65.5, the Benchmark Dose approach was applied to the resulting flow cytometric datasets. With “compound” serving as covariate, all eight compounds were combined into a single analysis, per time point and endpoint. The resulting 90% confidence intervals, plotted in Log scale, were considered as the potency rank for the eight compounds. The in vitro MultiFlow data showed a maximum confidence interval span of 1Log, which indicates data of good quality. Patterns observed in the compound potency rank were scrutinized by using the expert rule‐based software program Derek Nexus, developed by Lhasa Limited. Compound sub‐classification and structural alerts were considered contributory to the potencies observed for the topoisomerase II poisons studied herein. The Topo II poison Adverse Outcome Pathway was evaluated with MultiFlow endpoints serving as Key Events. The step‐wise approach described herein can be considered as a foundation for risk assessment of compounds within a specific mode of action of interest. Environ. Mol. Mutagen. 2020. © 2020 Wiley Periodicals, Inc.

Wheeldon, Ryan P.↗
DOE OSTI2013

Iliac Artery Stent Placement Relieves Claudication in Patients with Iliac and Superficial Femoral Artery Lesions

Purpose. To evaluate the efficacy of iliac artery stent placement for relief of claudication in patients with both iliac and superficial femoral artery (SFA) lesions. Methods. Stent placement for only iliac artery occlusive disease was performed in 94 limbs (74 patients) with both iliac and SFA occlusive disease on the same limb. All procedures were performed because intermittent claudication did not improve after continuation of antiplatelet medication therapy and home-based exercise for 3 months. Rutherford classification was 2 in 20 limbs and 3 in 74 limbs. Patients with critical limb ischemia were excluded. Median duration of follow-up was 40 months. Primary patency rates of the iliac stent, clinical improvement rates, and risk factors for requiring additional SFA procedures were evaluated. Results. Primary patency rates of the iliac stent at 1, 3, 5, and 7 years were 97, 93, 79, and 79 %, respectively. The initial clinical improvement rate was 87 %. Continued clinical improvement rates at 1, 3, 5, and 7 years were 87, 81, 69, and 66 %, respectively. SFA Trans-Atlantic Inter-Society Consensus (TASC) II C/D lesion was a significant risk factor for requiring additional SFA procedures. Conclusion. Intermittent claudication was relieved by iliac stent placement in most patients with both iliac and SFA lesions. Thus, the indications for treatment of the SFA intended for claudicants should be evaluated after treatment of the iliac lesion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Assessment of beating parameters in human induced pluripotent stem cells enables quantitative in vitro screening for cardiotoxicity

Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes show promise for screening during early drug development. Here, we tested a hypothesis that in vitro assessment of multiple cardiomyocyte physiological parameters enables predictive and mechanistically-interpretable evaluation of cardiotoxicity in a high-throughput format. Human iPSC-derived cardiomyocytes were exposed for 30 min or 24 h to 131 drugs, positive (107) and negative (24) for in vivo cardiotoxicity, in up to 6 concentrations (3 nM to 30 uM) in 384-well plates. Fast kinetic imaging was used to monitor changes in cardiomyocyte function using intracellular Ca{sup 2+} flux readouts synchronous with beating, and cell viability. A number of physiological parameters of cardiomyocyte beating, such as beat rate, peak shape (amplitude, width, raise, decay, etc.) and regularity were collected using automated data analysis. Concentration–response profiles were evaluated using logistic modeling to derive a benchmark concentration (BMC) point-of-departure value, based on one standard deviation departure from the estimated baseline in vehicle (0.3% dimethyl sulfoxide)-treated cells. BMC values were used for cardiotoxicity classification and ranking of compounds. Beat rate and several peak shape parameters were found to be good predictors, while cell viability had poor classification accuracy. In addition, we applied the Toxicological Prioritization Index (ToxPi) approach to integrate and display data across many collected parameters, to derive “cardiosafety” ranking of tested compounds. Multi-parameter screening of beating profiles allows for cardiotoxicity risk assessment and identification of specific patterns defining mechanism-specific effects. These data and analysis methods may be used widely for compound screening and early safety evaluation in drug development. - Highlights: • Induced pluripotent stem cell-derived cardiomyocytes are promising in vitro models. • We tested if evaluation of cardiotoxicity is possible in a high-throughput format. • The assay shows benefits of automated data integration across multiple parameters. • Quantitative assessment of concentration–response is possible using iPSCs. • Multi-parametric screening allows for cardiotoxicity risk assessment.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2024

San Joaquin Valley Health & Air Quality II: Assessing Urban Heat Island Distribution and its Intersections with Air Quality to Understand Converging Vulnerabilities

The city of Stockton, California, located within the San Joaquin Valley (SJV), is a major hub for agricultural production and has endured the continuous threat to community health from nitrogen dioxide (NO 2 ) and increasing temperatures. The convergence of these issues occurs within historically segregated communities that are disproportionately facing health risks related to heat and air quality. Little Manila Rising (LMR), a social and environmental justice (EJ) advocacy non-profit, partnered with NASA DEVELOP for a second term project to evaluate county wide urban heat islands, sociodemographic vulnerability, landcover classification, and the convergence of these variables. We utilized Landsat 8 Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI) data to produce a land surface temperature (LST) and Normalized Difference Vegetation Index map. They added Centers for Disease Control (CDC) socioeconomic data from 2020 to identify which communities in Stockton were more susceptible to these environmental factors. Additionally, we used NAIP imagery to create a landcover map differentiating developed infrastructure from tree canopy cover. We discovered that south Stockton, where LMR resides, had the worst convergence of heat, air pollution, low canopy coverage and sociodemographic vulnerability compared to northern and rural parts of the city. This was further substantiated by statistical analysis showing a strong positive relationship between areas of high LST and low vegetation. The results provided LMR with compelling evidence to use in their EJ advocacy, and in their efforts to inform state officials of the discriminatory issues they face.

Urban Heat Islands↗
DOE OSTI2022

Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Clinical Importance of Sputum in the Respiratory Tract as a Predictive Marker of Postoperative Morbidity After Esophagectomy for Esophageal Cancer

Background: Respiratory morbidity is common after esophagectomy and can be a major cause of surgery-related mortality. Thus, it is important to identify novel predictors that can preoperatively estimate the incidence of postoperative respiratory morbidity. Asymptomatic sputum in the respiratory tract is sometimes observed on preoperative computed tomography (CT). This study aimed to determine the clinical importance of sputum in the respiratory tract as a predictor of postoperative morbidity after esophagectomy for esophageal cancer. Patients and Methods: The study included 609 consecutive patients who underwent three-incisional esophagectomy for esophageal cancer between April 2005 and November 2018. Results: Among the patients, 76 (12.5%) had sputum in the respiratory tract on preoperative CT. This finding was significantly associated with older age, more extreme smoking habit, worse performance status, lower forced expiratory volume 1%, and more frequent pulmonary comorbidities. Additionally, the incidence of postoperative pneumonia was higher in these patients than in those without sputum (16 vs 8%, p = 0.028). Sputum in the main bronchus was associated with higher frequencies of morbidity of Clavien–Dindo classification (CDc) ≥ II (p = 0.019), severe morbidity of CDc ≥ IIIb (p = 0.058), pneumonia (p = 0.10), and pulmonary morbidity (p = 0.19) compared with the finding of sputum in the trachea alone. On multivariate analysis, sputum in the respiratory tract was an independent risk factor (hazard ratio, 2.07; 95% confidence interval, 1.019–4.207; p = 0.044) for postoperative pneumonia. Conclusions: Sputum in the respiratory tract is a novel predictor of postesophagectomy pneumonia. Patients with sputum in the more distal respiratory tract might have high risk of postoperative morbidities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2002

Interpretation and classification of microvolt T wave alternans tests

Measurement of microvolt-level T wave alternans (TWA) during routine exercise stress testing now is possible as a result of sophisticated noise reduction techniques and analytic methods that have become commercially available. Even though this technology is new, the available data suggest that microvolt TWA is a potent predictor of arrhythmia risk in diverse disease states. As this technology becomes more widely available, physicians will be called upon to interpret microvolt TWA tracings. This review seeks to establish uniform standards for the clinical interpretation of microvolt TWA tracings.

NASA Discipline Cardiopulmonary↗
NASA NTRS2022

Exploring Applications of Machine Learning for Wildfire Monitoring and Detection using Unmanned Aerial Vehicles

Wildfires are increasing in frequency and severity around the world, including the United States. The losses caused by wildfires could be mitigated if high-risk areas, hotspots, and flare-ups could be monitored continuously, such as through the use of Unmanned Aerial Vehicles (UAVs). This paper documents exploratory efforts using machine learning to determine efficient flight paths for UAVs and to detect wildfires using image classification. On path planning, three machine learning techniques—Genetic Algorithm, Simulated Annealing, and Dynamic Programming—were explored. Genetic Algorithm was found to be an effective approach for path planning for wildfire monitoring and surveillance by UAVs. For a scenario of 25 locations in a circular arrangement, the algorithm was able to return the optimal path. The accuracy and execution time was found to be sensitive to the algorithm hyperparameters selected, which was especially evident in scenarios with hundreds or thousands of locations. Simulated Annealing was also found to be an effective approach for UAV path planning, with a major benefit of avoiding getting trapped in local minima and being straightforward to implement. Like Genetic Algorithm, the performance of Simulated Annealing was also found to be sensitive to the algorithm hyperparameters selected. By comparison, Dynamic Programming guarantees optimality for any number of locations, but it was found to be less practical in terms of execution time for scenarios with more than about a couple dozen locations. On wildfire detection, image classification using deep learning with a convolutional neural network was explored. Transfer learning was found to be a useful technique to efficiently train deep learning models. Also, it was determined that GPU processing can increase training speed by an order of magnitude, which enables significantly faster development. For a validation test set of 500 images, there were only two false negatives and zero false positives. These results demonstrate that detecting wildfires in static cameras using machine learning is feasible and establish a baseline for using images captured by UAVs in flight for wildfire detection.

Wildfire management↗
NASA NTRS2022

Dusty Environment Classification and Testing: Dust Mitigation Slide Wipes & Tapes

During the Apollo missions many mechanisms, equipment, and surfaces were contaminated by lunar dust and often negatively affected. The methods used to clear these devices of dust proved ineffective, which led to premature failure in some cases. Systems being designed for upcoming missions to the Moon will need to address the performance degradation risk of dust contamination. Surfaces at risk include thermal control surfaces, solar cells, camera and sensor optics, seals, metal joints and tools, and space suit assemblies. To improve state of the art dust mitigation approaches, the dust mitigation team at NASA Glenn Research Center (GRC) explored the effects imposed on substrates during cleaning activities in the presence of lunar dust. The Uniform Dust Deposition System (UDDS) was used to conduct a study of various cleaning techniques on different substrates. Test substrates and cleaning media were selected to represent a wide range of structural and functional materials. Substrates included orthofabric, thermal radiator coating, aluminum, quartz glass, silicone rubber, aluminized Mylar, and FEP. Cleaning materials included cloth wipes, tapes, a brush, and a pliable cleaner concept. Cleaning material / substrate pairs were rated on cleaning efficiency, substrate damage, cleaning material longevity, and ease of use. The best performing cleaning method varied based on application.

lunar simulant↗
DOE OSTI2015

Review of Fissile Material Exemptions and General Licenses in 10 CFR Part 71 - 14578

Title 10 of the United States (US) Code of Federal Regulations (CFR), Part 71, Packaging and Transportation of Radioactive Material includes requirements for the transport of fissile material in packages. These regulations provide requirements for packaging that is certified by the US Nuclear Regulatory Commission (NRC) to transport fissile material, but the regulations also include provisions that allow for shipment of fissile material in packages that are not required to be certified by the NRC. These provisions include criteria for exemptions from classification as fissile material (10 CFR 71.15) and permit general licenses for limited quantities of fissile material and plutonium-beryllium special form sources (10 CFR 71.22 and 10 CFR 71.23, respectively). These regulations were revised by NRC as part of a broad rulemaking effort in 2004. These regulations are used frequently for a wide-variety of fissile material shipping operations and shippers must interpret the regulations for particular shipping situations. The quantity of fissile material that presents a criticality safety risk depends on the other materials in the system that might absorb neutrons emitted from fission or moderate (slow) those neutrons to lower energies where the probability of them creating an additional fission is highest. Besides the absorption and moderation of neutrons, other parameters that must be considered to ensure criticality safety are: the mass, concentration, or isotopic distribution of the fissile material; and the system geometry and neutron reflection of the package from surrounding materials. These parameters were carefully considered in developing the requirements for the exemptions from the classification of fissile material and the requirements for general licenses for fissile material. This paper will review the technical basis, intent, and anticipated usage of each of the fissile material exemption and general license provisions. Additionally, this paper will discuss the recent regulatory history of the Part 71 fissile material exemptions and general licenses, including the 2015 rulemaking effort. Finally, this paper will outline an upcoming NUREG/CR document regarding the fissile material exemptions and general licenses, and discuss recommendations that are being formulated for potential future revisions to the regulations. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Dusty Environment Classification and Testing: Dust Mitigation Slide Cleaning Material Study

During the Apollo missions many mechanisms, equipment, and surfaces were contaminated by lunar dust and often negatively affected. The methods used to clear these devices of dust proved ineffective, which led to premature failure in some cases. Systems being designed for upcoming missions to the Moon will need to address the performance degradation risk of dust contamination. Surfaces at risk include thermal control surfaces, solar cells, camera and sensor optics, seals, metal joints and tools, and space suit assemblies. To improve state of the art dust mitigation approaches, the dust mitigation team at NASA Glenn Re-search Center (GRC) explored the effects imposed on substrates during cleaning activities in the presence of lunar dust. The Uniform Dust Deposition System (UDDS) was used to conduct a study of various cleaning techniques on different substrates. Test substrates and cleaning media were selected to represent a wide range of structural and functional materials. Substrates included orthofabric, thermal radiator coating, aluminum, quartz glass, silicone rubber, aluminized Mylar, and FEP. Cleaning materials included cloth wipes, tapes, a brush, and a pliable cleaner concept. Cleaning material / substrate pairs were rated on cleaning efficiency, substrate damage, cleaning material longevity, and ease of use. The best performing cleaning method varied based on application.

dust mitigation↗
NASA NTRSDate not supplied

Assessing Land Cover Change Dynamics in the Peruvian Amazon to Map Outbreak Risk and Inform Public Health Interventions for Zoonotic Disease Prevention

Dengue fever and leishmaniasis are two tropical diseases prevalent in Madre de Dios Region of Peru and have been associated with urbanization and road construction. Rapid land use changes such as mining, timber harvesting, and hydroelectric dam development lead to denser human presence in previously sparsely-populated areas which increases the proximity of human settlements to zoonotic disease vectors. In partnership with the Peruvian Ministries of Health (MINSA), the Environment (MINAM), and other in-country collaborators, a NASA DEVELOP team examined Land Use Land Cover (LULC) changes and reported dengue and leishmaniasis incidence in the Madre de Dios region. This sought to help MINSA and MINAM understand the spatial relationship between land use change and zoonotic disease incidence. We created a LULC classification script using Google Earth Engine (GEE) with Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) imagery to classify land cover in 2010, 2015, and 2020 and evaluate changes over this time period. The team then compared the quantified results of the LULC assessment in conjunction with reported disease cases to evaluate disease incidence and key land cover changes across Madre de Dios’s 11 districts. Follow on work will use these products to develop more detailed outbreak risk maps. These products will allow MINSA, MINAM, and other partners to understand hotspots of land cover change in Peru and the relationship with outbreaks to inform public health decision makers and environmental policy.

Nataly Chacon-Buitrago↗
NASA NTRS2007

Modeling Malaria Transmission in Thailand and Indonesia

Malaria Modeling and Surveillance is a project in the NASA Applied Sciences Public Health Applications Program. The main objectives of this project are: 1) identification of the potential breeding sites for major vector species: 2) implementation of a malaria transmission model to identify they key factors that sustain or intensify malaria transmission; and 3) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity. Remote sensing and GIs are the essential elements of this project. The NASA Earth science data sets used in this project include AVHRR Pathfinder, TRMM, MODIS, NSIPP and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of precipitation, temperatures, humidity and vegetation. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Examples for spatio-temporal modeling of malaria transmissions in Southeast Asia are given. Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to Southeast Asia. The model and techniques are equally applicable to other regions of the world, when appropriate epidemiological and vector ecological parameters are used as input.

Kiang, Richard↗
NASA NTRS2010

Certification

Objective 1: Provide regulators with a methodology for development of airworthiness requirements for certification of UAS. a) Rationale: a comprehensive methodology does not currently exist to support development of regulation for certification of UAS. Regulation is essential to enable routine access to the NAS. b) Approach: 1) assess existing approaches and classification schemes for deriving acceptable means of compliance to airworthiness requirements. 2) investigate a service-based approach to classification of UAS. 3) conduct comparative analysis of different methodologies. 4) work with FAA to determine best approach and conduct case study. 5) participate in regulatory/standards organizations developing safety and performance requirements for UAS. Objective 2: Provide regulators and industry with hazard and risk-related data to support criteria for UAS type design. a) Rationale: There is presently little UAS specific data (incident, accident, and reliability), especially in a civil context, to support risk assessment and development of standards and regulation. b) Approach: Identify gaps in existing data, provide measured data as needed, and formulate recommendations by: 1) evaluating UAS incident/accident data collection efforts and determining additional support necessary for regulation. 2) assessing UAS-specific hazards and risks. 3) evaluating need for reliability data for UAS-unique systems, components and subsystem, and determining additional measurement requirements. 4) developing guidance and best practices for UAS type design.

Hayhurst, Kelly↗
NASA NTRSDate not supplied

Collaborative Communications Between a Human and a Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACC to which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced Air Mobility,↗
NASA NTRS2021

Collaborative Communications Between A Human and A Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACCto which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced air mobility↗
NASA NTRS2016

Taxonomies and Albedos of Near-Earth Asteroids

Characterizing near-Earth asteroids (NEAs) can help to assess the risk of possible impactors. Over many decades, asteroids have been spectrally classified into numerous taxonomic systems, most notably those of Tholen, Bus, and Bus-DeMeo. By mapping these various taxonomic systems to broader categories called complexes, it is easier to study the relationship between classifications and other physical parameters. There has recently been an increase in the number of objects with measured albedos which is advantageous for characterization because the albedo and absolute magnitude can be used to determine diameter. Knowing an asteroids diameter helps us better understand dangers they may pose.

Napier, Kate↗