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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2014

Environmental and Socio-Demographic Determinants of Dengue Fever in Colombo City, Sri Lanka

Dengue fever has increased exponentially in Sri Lanka, from 24.4 cases per 100,000 in 2003 to 165.3 per 100,000 population in 2013. Although early warning systems using predictor models have been previously developed in other settings, it is important to develop such models in each local setting. Further, the ability of these models to be applicable at smaller geographic units will enhance current vector control and disease surveillance measures. The aim of this paper was to identify environmental and socio-economic status (SES) risk factors that may predict dengue fever at the Gram Niladhari Divisions (GND) level (smallest administrative unit) in Colombo city, Sri Lanka. These factors included landcover classes, amount of vegetation, population density, water access and neighborhood SES as determined by roof type. A geographically weighted regression (GWR) was used to develop the prediction model. A total 55 GND units covering an area of 37 sq km were investigated. We found that GND units with decreased vegetation, higher built-up area, higher population density and poor access to tap-water supply were associated with high risk of dengue; the pertinent GND units were concentrated in the center of the city. This is the first study in Sri Lanka to include both environmental and socio-demographic factors in prediction models for dengue fever. The methodology may be useful in enhancing ongoing dengue fever control measures in the country, and to be extended to other countries in the region that have an increasing incidence of dengue fever.

Tipre, Meghan↗
NASA NTRS2017

Risk of Cardiac Rhythm Problems During Spaceflight

NASA has concerns regarding the incidence and clinical significance of cardiac arrhythmias that could occur during long-term exposure to the spaceflight environment, such as on the International Space Station (ISS) or during a prolonged (e.g., up to 3 years) sojourn to Mars or on the Moon. There have been some anecdotal reports and a few documented cases of cardiac arrhythmias in space, including one documented episode of non-sustained ventricular tachycardia. The potential catastrophic nature of a sudden cardiac death in the remote space environment has led to concerns from the early days of the space program that spaceflight might be arrhythmogenic. Indeed, there are known and well-defined changes in the cardiovascular system with spaceflight: a) plasma volume is reduced, b) left ventricular mass is decreased, and c) the autonomic nervous system adapts to the weightless environment. Combined, these physiologic adaptations suggest that changes in cardiac structure and neuro-humoral environment during spaceflight could alter electrical conduction, although the evidence supporting this contention consists mostly of minor changes in QT interval (the time between the start of the Q wave and the end of the T wave on an electrocardiogram tracing) in a small number of astronauts after long-duration spaceflight. Concurrent with efforts by NASA Medical Operations to refine and improve screening techniques relevant to arrhythmias and cardiovascular disease, as NASA enters the era of exploration-class missions it will be critical to determine with the highest degree of certainty whether spaceflight by itself alters cardiac structure and function sufficiently to increase the risk of arrhythmias.

Lee, Stuart M. C.↗
NASA NTRS1992

SAR backscatter from coniferous forest gaps

A study is in progress comparing Airborne Synthetic Aperture Radar (AIRSAR) backscatter from coniferous forest plots containing gaps to backscatter from adjacent gap-free plots. Issues discussed are how do gaps in the range of 400 to 1600 sq m (approximately 4-14 pixels at intermediate incidence angles) affect forest backscatter statistics and what incidence angles, wavelengths, and polarizations are most sensitive to forest gaps. In order to visualize the slant-range imaging of forest and gaps, a simple conceptual model is used. This strictly qualitative model has led us to hypothesize that forest radar returns at short wavelengths (eg., C-band) and large incidence angles (e.g., 50 deg) should be most affected by the presence of gaps, whereas returns at long wavelengths and small angles should be least affected. Preliminary analysis of 1989 AIRSAR data from forest near Mt. Shasta supports the hypothesis. Current forest backscatter models such as MIMICS and Santa Barbara Discontinuous Canopy Backscatter Model have in several cases correctly predicted backscatter from forest stands based on inputs of measured or estimated forest parameters. These models do not, however, predict within-stand SAR scene texture, or 'intrinsic scene variability' as Ulaby et al. has referred to it. For instance, the Santa Barbara model, which may be the most spatially coupled of the existing models, is not truly spatial. Tree locations within a simulated pixel are distributed according to a Poisson process, as they are in many natural forests, but tree size is unrelated to location, which is not the case in nature. Furthermore, since pixels of a simulated stand are generated independently in the Santa Barbara model, spatial processes larger than one pixel are not modeled. Using a different approach, Oliver modeled scene texture based on an hypothetical forest geometry. His simulated scenes do not agree well with SAR data, perhaps due to the simple geometric model used. Insofar as texture is the expression of biological forest processes, such as succession and disease, and physical ones, such as fire and wind-throw, it contains useful information about the forest, and has value in image interpretation and classification. Forest gaps are undoubtedly important contributors to scene variance. By studying the localized effects of gaps on forest backscatter, guided by our qualitative model, we hope to understand more clearly the manner in which spatial heterogeneities in forests produce variations in backscatter, which collectively give rise to scene texture.

Day, John L.↗