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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Cardiovascular Disease Outcomes Among the NASA Astronaut Corps

BACKGROUND: Acute effects of spaceflight on the cardiovascular system have been studied extensively, but the combined chronic effects of spaceflight and aging are not well understood. Preparation for and participation in spaceflight activities are associated with changes in the cardiovascular system such as decreased carotid artery distensibility and decreased ventricular mass which may lead to an increased risk of cardiovascular disease. Additionally, astronauts who travel into space multiple times or for longer durations may be at an increased risk across their lifespan. To that end, the purpose of this study was to determine the incidence of common cardiovascular disease (CVD) outcomes among the NASA astronaut corps during their active career and through retirement. METHODS: Cardiovascular disease outcomes were defined as reports of any of the following: myocardial infarction (MI), revascularization procedures (coronary artery bypass graft surgery [CABG] or percutaneous coronary intervention [PCI]), hypertension, stroke or transient ischemic attack [TIA], heart failure, or total CVD (as defined by the AHA - combined outcome of MI, Angina Pectoris, heart failure, stroke, and hypertension). Each outcome was identified individually from review of NASA's Electronic Medical Record (EMR), EKG reports, and death certificates using ICD-9 codes as well as string searches of physician notes of astronaut exams that occurred between 1959 and 2016. RESULTS: Of 338 NASA astronauts selected as of 2016, 9 reported an MI, 12 reported a revascularization procedure, (7 PCI and 5 CABG), 4 reported Angina (without MI), 5 reported heart failure, 9 reported stroke/TIA, and 96 reported hypertension. Total CVD was reported in 105 astronauts. No astronaut who had an MI or revascularization procedure flew a spaceflight mission following the event. All MI, revascularization, and stroke events occurred in male astronauts. When reviewing astronaut ECG reports, abnormal ECG reports were found in only 8% of records (n=430) and mainly among retired astronauts (82%), with marked sinus bradycardia being the reason for the abnormal classification.

Charvat, Jacqueline M.↗
NASA NTRS2011

Collaborative Clustering for Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

Wagstaff. Loro :/↗
NASA NTRS2007

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment 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 the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are 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 the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗
NASA NTRS2003

Performance Evaluation Modeling of Network Sensors

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

probability of detection↗
NASA NTRS2014

A Multi-Wavelength Investigation of the Radio-Loud Supernova PTF11qcj and its Circumstellar Environment

We present the discovery, classification, and extensive panchromatic (from radio to X-ray) follow-up observations of PTF11qcj, a supernova (SN) discovered by the Palomar Transient Factory (PTF). Our observations with the Karl G. Jansky Very Large Array show that this event is radio-loud: PTF11qcj reached a radio peak luminosity comparable to that of the famous gamma-ray-burst-associated SN 1998bw (L (sub 5 gigahertz) approximates 10 (sup 29) ergs per second per hertz). PTF11qcj is also detected in X-rays with the Chandra Observatory, and in the infrared band with Spitzer. Our multi-wavelength analysis probes the SN interaction with circumstellar material. The radio observations suggest a progenitor mass-loss rate of approximately 10 (sup -4) the mass of the sun per year times (v (sub omega) divided by 1000 kilometers per second), and a velocity of approximately 0.3-0.5 c (the speed of light in a vacuum) for the fastest moving ejecta (at around 10 days after explosion). However, these estimates are derived assuming the simplest model of SN ejecta interacting with a smooth circumstellar wind, and do not account for possible inhomogeneities in the medium and asphericity of the explosion. The radio data show deviations from such a simple model, as well as a late-time re-brightening. The X-ray flux from PTF11qcj is compatible with the high-frequency extrapolation of the radio synchrotron emission (within the large uncertainties). A light echo from pre-existing dust is in agreement with our infrared data. Our pre-explosion data from the PTF suggest that a precursor eruption of absolute magnitude M (sub r) approximately equal to -13 mag may have occurred approximately 2.5 years prior to the SN explosion. Overall, PTF11qcj fits the expectations from the explosion of a Wolf-Rayet star. Precursor eruptions may be a feature characterizing the final pre-explosion evolution of such stars.

Radio↗
NASA NTRS1990

(Ar-39)-(Ar-40) dating of mesosiderites - Evidence for major parent body disruption less than 4 Ga ago

The (Ar-39) (Ar-40) chronologies were determined for 14 different mesosiderites representing the full range of classification according to recrystallization, and these chronologies were compared with analogous data for other meteorite types and for lunar highland rocks. Results of Ar-Ar chronologies indicate the history of a degassing of Ar due to a major thermal event that occurred less than 3.9 Ga ago; this event is not the metal-silicate mixing event, which is known to have occurred earlier than 4.4 Ga ago. It is suggested that a major collisional disruption-reassembly event less than 3.9 Ga ago took place, leaving the metal-silicate breccias buried under tens of kilometers of rubble, where they cooled slowly through the Ar closure temperatures.

Bogard, D. D.↗
NASA NTRS2022

Arizona Water Resources Ii: Utilizing Aerial Imagery and Nasa Earth Observations to Assess Pinyon-Juniper Tree Mortality in Flagstaff, AZ

Pinyon-juniper woodlands (PJW) provide critical and resilient habitat for the local mammal and small bird species of Arizona's northern xeric environment. Drought in Arizona has been persistent for many decades, yet in 2021 PJW experienced a mass tree mortality event at the Wupatki National Monument (WNM) and in other areas across the American Southwest. Previously, researchers at the National Park Service (NPS) and the team from the NASA DEVELOP National Program attempted to quantify the extent of mortality in Northern Arizona between 2015 and 2021 using high resolution National Agricultural Imagery Program (NAIP) aerial photographs. This project aimed to improve the previous term’s methodology and expanded the comparison of the post-mortality event in 2021 to include tree cover assessments for 2017 and 2019. In this iteration, the team utilized NAIP imagery in conjunction with Landscape Fire and Resource Management Planning Tools (LANDFIRE) to calculate the total difference in PJW mortality using an unsupervised classification model trained from multi-date Modified Soil-Adjusted Vegetation Index (MSAVI) and the Visible Atmospherically Resistant Index (VARI) data for the study area. The research also assessed correlations between tree mortality and environmental factors using Western Land Data Assimilation System (WLDAS) modelled climate data. Average PJW mortality from 2015 to 2021 was 21.63% including 19.8% in WNM with the vast majority of dieback occurring between 2019 and 2021. The correlations were weak with the most correlated variables being bare soil evaporation (0.15), rainfall (0.14), groundwater storage (0.13), and wind speed (0.12), perhaps indicating drought as a likely driver of PJW mortality.

pinyon-juniper woodlands↗
NASA NTRS1971

Pyrotechnic hazards classification and evaluation program test report. Heat flux study of deflagrating pyrotechnic munitions

A heat flux study of deflagrating pyrotechnic munitions is presented. Three tests were authorized to investigate whether heat flux measurements may be used as effective hazards evaluation criteria to determine safe quantity distances for pyrotechnics. A passive sensor study was conducted simultaneously to investigate their usefulness in recording events and conditions. It was concluded that heat flux measurements can effectively be used to evaluate hazards criteria and that passive sensors are an inexpensive tool to record certain events in the vicinity of deflagrating pyrotechnic stacks.

Fassnacht, P. O.↗
NASA NTRS1986

Stratospheric dust collections: Valuable resources for space and atmospheric scientists

The stratospheric collection at the Johnson Space Center Curatorial Facility offers a unique opportunity to study well-documented, individual particles (or groups of particles) from a wide variety of sources. The nature of the collection and curation process, as well as the timeliness of some sampling periods, ensures that all data obtained from stratospheric particles is a valuable resource for scientists from a wide range of disciplines. A few samples of the uses of these stratospheric dust collections are outlined. An understanding of global parameters at a particular point in time in the stratosphere can be obtained from a study of complete collection surfaces. For example, an accurate assessment of particle concentration over a wide range of sizes was experimentally determined for the stratospheric cloud formed one month after the eruption of El Chichon. Additional studies on the El Chichon cloud over a six-month period showed that volcanic ash settles out of the stratosphere at a rate determined primarily by particle shape and density. Another study during a volcanically quiescent period has shown that total particle number density during the summer of 1981 was approx. 2.7 x 10(-1) cm(-3), for particles 1 micron diameter. However, 95% of these particles were 5 micrometers diameter. With the above classification scheme, an estimate of micrometeorite number density at 20km altitude can also be made. Continuation of these types of studies, for shorter collection periods at regular intervals, can provide important experimental data on the contributions of orbital debris, rocket firings and transient events on the total stratospheric particle budget.

Mackinnon, I. D. R.↗
NASA NTRS1994

The effect of repeating gamma-ray bursts on V/V(sub max)

I consider the effect of repeating burst sources on the the mean value of V/V(sub max) statistic. I find that if the burst sources are distributed homogeneously in a d-dimensional space, the mean value of V/V(sub max) converges to d/(d+3) as long as the luminosity function is dependent of position. Choosing the brightest event from a cluster of k events shifts the luminosity function to higher luminosities, but if the original luminosity function is position independent, it remains so. Therefore the treatment of repeating events, if applied consistently, will not affect the effectiveness the mean value of V/V(sub max) as a test of burst homogeneity. The calculation of the mean value of V/V(sub max) for apparent repeating and non-repeating source populations will be raised by the incorrect classification of faint bursts. In conclusion, the current practice of calculating the mean value of V/V(sub max) using all bursts, even apparent repeaters, and treating multispike bursts as single bursts, is valid and consistent.

Band, David L.↗
NASA NTRS2021

Swift/UVOT Follow-Up of Gravitational Wave Alerts in the O3 Era

In this paper, we report on the observational performance of the Swift Ultra-violet/Optical Telescope (UVOT) in response to the gravitational wave (GW) alerts announced by the Advanced Laser Interferometer Gravitational Wave Observatory and the Advanced Virgo detector during the O3 period. We provide the observational strategy for follow-up of GW alerts and provide an overview of the processing and analysis of candidate optical/UV sources. For the O3 period, we also provide a statistical overview and report on serendipitous sources discovered by Swift/UVOT. Swift followed 18 GW candidate alerts, with UVOT observing a total of 424 deg2. We found 27 sources that changed in magnitude at the 3σ level compared with archival u- or g-band catalogued values. Swift/UVOT also followed up a further 13 sources reported by other facilities during the O3 period. Using catalogue information, we divided these 40 sources into five initial classifications: 11 candidate active galactic nuclei (AGNs)/quasars, three cataclysmic variables (CVs), nine supernovae, 11 unidentified sources that had archival photometry, and six uncatalogued sources for which no archival photometry was available. We have no strong evidence to identify any of these transients as counterparts to the GW events. The 17 unclassified sources are likely a mix of AGN and a class of fast-evolving transient, and one source may be a CV.

gravitational waves↗
NASA NTRS1982

Forest management applications of Landsat data in a geographic information system

The utility of land-cover data resulting from Landsat MSS classification can be greatly enhanced by use in combination with ancillary data. A demonstration forest management applications data base was constructed for Santa Cruz County, California, to demonstrate geographic information system applications of classified Landsat data. The data base contained detailed soils, digital terrain, land ownership, jurisdictional boundaries, fire events, and generalized land-use data, all registered to a UTM grid base. Applications models were developed from problems typical of fire management and reforestation planning.

Maw, K. D.↗
NASA NTRS2018

Interactive Multi-Instrument Database of Solar Flares

The fundamental motivation of the project is that the scientific output of solar research can be greatly enhanced by better exploitation of the existing solar/heliosphere space-data products jointly with ground-based observations. Our primary focus is on developing a specific innovative methodology based on recent advances in "big data" intelligent databases applied to the growing amount of high-spatial and multi-wavelength resolution, high-cadence data from NASA's missions and supporting ground-based observatories. Our flare database is not simply a manually searchable time-based catalog of events or list of web links pointing to data. It is a preprocessed metadata repository enabling fast search and automatic identification of all recorded flares sharing a specifiable set of characteristics, features, and parameters. The result is a new and unique database of solar flares and data search and classification tools for the Heliophysics community, enabling multi-instrument/multi-wavelength investigations of flare physics and supporting further development of flare-prediction methodologies.

Heliophysics↗
NASA NTRS1973

A summary of major NASA launchings, 1 October 1958 - 30 September 1973

This report was compiled from several different sources. Documents consulted included: Operations Summaries, post-launch Flash Flight Reports, Final Field Reports, Mission Operations Reports (both pre-launch and post-launch), and Satellite Situation Reports. Other major references were publications of the NASA Historical Office, such as: Aeronautics and Astronautics 1916-1960; Aeronautical and Astronautical Events of 1961-1962; Aeronautics and Astronautics (yearly editions since 1963); and NASA's Pocket Statistics (published monthly.) The report is divided into projects within broad mission categories, with each project being treated chronologically. Mission results have been categorized as: successful (S); unsuccessful (U); or, partially successful (P). These are arbitrary classifications, made after a comparison of objectives and actual results.

Source record↗
NASA NTRS1993

Identification of two classes of gamma-ray bursts

We have studied the duration distribution of the gamma-ray bursts of the first BATSE catalog. We find a bimodality in the distribution, which separates GRBs into two classes: short events (less than 2 s) and longer ones (more than 2 s). Both sets are distributed isotropically and inhomogeneously in the sky. We find that their durations are anticorrelated with their spectral hardness ratios: short GRBs are predominantly harder, and longer ones tend to be softer. Our results provide a first GRB classification scheme based on a combination of the GRB temporal and spectral properties.

Kouveliotou, Chryssa↗
NASA NTRS1993

Giant radiating dyke swarms on Earth and Venus

On Earth, giant radiating dyke swarms are usually preserved as fan-shaped fragments which have been dismembered from their original configuration by subsequent plate tectonic rifting events. Analysis of the largest fragments and consideration of their original configuration has led to the idea that many swarms are plume related, and that dyke swarms radiate away from plume centers. Magellan radar data reveal abundant intact giant radiating swarms on Venus which are similar in scale and pattern to those on Earth. The absence of intense weathering and plate tectonic processes on Venus accounts for the preservation of the primary radiating patterns. It is characteristic of both Earth and Venus that giant radiating dikes are emplaced laterally for distances of at least 2000 km away from plume centers. At distances beyond the influence of the plume on both Earth and Venus, the radiating dyke pattern is often swept into a linear pattern aligned with the regional stress field. There is tremendous potential synergism between the characterization and analysis of terrestrial dyke swarms (where significant erosion has revealed their structure and emplacement directions at depth) and the giant swarms of Venus (where the complete circumferential structure is preserved, and the surface fracture systems above near surface dikes and the nature of the central source regions are revealed). In this study, we report on the characteristics of radial dyke swarms on Earth and Venus and draw some preliminary comparisons from the two perspectives. In summary, on both planets there is evidence for plume-related magmatic centers associated with vertical and lateral injection of magma over considerable distances (up to at least 2000 km). The abundance of very broadly radiating swarms on Venus supports the notion that the swarms on Earth were radiating over broad sectors at the time of intrusion but were dissected by later events. The Venus data show that a swarm can change from radiating (proximal) to regional (distal) subparallel orientations. An implication for Earth is that many regional linear swarms which do not have a radiating pattern may be due to fragmentation of the swarm during later plate tectonic rifting. Completion of the global classification and census of Venus features, comparison to the terrestrial synthesis, and documentation of the mode of emplacement of dikes in these environments (buffered and unbuffered conditions) should lead to additional general insight into mechanisms of formation and evolution and their relation to plumes.

Ernst, Richard E.↗
NASA NTRS1989

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

Ali, Moonis↗
NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗