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In computer program NOROCA populations statistics from National Center for Health Statistics used with computational procedure to estimate health service utilization rates, physician demands (by specialty) and hospital bed demands (by type of service). Computational procedure applicable to health service area of any size and even used to estimate statewide demands for health services.
Autocorrelated normal random variates were generated via computer and the effects of various levels of correlation on goodness of fit problems were studied. The results are useful in determining the distribution or estimating the parameters of populations that correlate observations such as wind speeds and temperature. The model used to generate the autocorrelated data is an autoregressive process of order 1. The Kolmogorov-Smirnov and chi-square statistics are used in the analysis. It was observed in the simulation that high positive correlations tend to shift the sample mean away from the population mean and negative correlations tend to shift the sample mean towards the population mean. In many cases, it was observed that positive and negative correlations tend to decrease the standard deviation. However, since this did not occur in all cases, no definite conclusion can be made regarding the standard deviation. Since the autoregressive process is a linear transformation, it is not surprising that normality was preserved. However, a possible extension of this problem could be to generate non-normal data and observe how the distribution is affected by correlation. Another extension might utilize another model such as autoregressive of order k or a moving average process of order k.
Any discussion of expanding the capabilities of Space Surveillance Networks to include tracking and cataloging smaller objects will require a good understanding of orbital debris. In the current U.S. catalog of over 11,000 objects, more than 50% are classified as "debris" to include fragmentation debris, operational debris, liquid metal coolant, and Westford needles. If the catalog is increased to 100,000 objects by lowering the tracked object size threshold, almost all of the additional objects will be orbital debris. The Orbital Debris Program Office has been characterizing the small orbital debris environment through measurements and modeling for many years. This presentation will specifically discuss two different studies conducted at NASA. The first study was done in 1992 and examined the requirements and produced a conceptual design for a Collision Avoidance Network to protect the Space Station Freedom from centimeter sized orbital debris while minimizing maneuvers. The second study was conducted last year and produced NASA s estimate of the orbital population for the years 2015 and 2030 for objects 2 cm and larger.
Space debris is a worldwide-recognized issue concerning the safety of commercial, military, and exploration spacecraft. The space debris environment includes both naturally occuring meteoroids and objects in Earth orbit that are generated by human activity, termed orbital debris. Space agencies around the world are addressing the dangers of debris collisions to both crewed and robotic spacecraft. In the United States, the Orbital Debris Program Office at the NASA Johnson Space Center leads the effort to categorize debris, predict its growth, and formulate mitigation policy for the environment from low Earth orbit (LEO) through geosynchronous orbit (GEO). This paper presents recent results derived from the NASA long-term debris environment model, LEGEND. It includes the revised NASA sodium potassium droplet model, newly corrected for a factor of two over-estimation of the droplet population. The study indicates a LEO environment that is already highly collisionally active among orbital debris larger than 1 cm in size. Most of the modeled collision events are non-catastrophic (i.e., They lead to a cratering of the target, but no large scale fragmentation.). But they are potentially mission-ending, and take place between impactors smaller than 10 cm and targets larger than 10 cm. Given the small size of the impactor these events would likely be undetectable by present-day measurement means. The activity continues into the future as would be expected. Impact rates of about four per year are predicted by the current study within the next 30 years, with the majority of targets being abandoned intacts (spent upper stages and spacecraft). Still, operational spacecraft do show a small collisional activity, one that increases over time as the small fragment population increases.
A remote sensing-based system has been developed to characterize the potential for rainfall-triggered landslides across the globe in near real-time. The Landslide Hazard Assessment for Situational Awareness (LHASA) model uses a decision tree framework to combine a static susceptibility map derived from information on slope, rock characteristics, forest loss, distance to fault zones and distance to road networks with satellite precipitation estimates from the Global Precipitation Measurement (GPM) mission. Since 2016, the LHASA model has been providing near real-time and retrospective estimates of potential landslide activity. Results of this work are available at https://landslides.nasa.gov. In order to advance LHASA’s capabilities to characterize landslide hazards and impacts dynamically, we have implemented a new approach that leverages machine learning, new parameters, and new inventories. LHASA 2.0 uses the XGBoost machine learning model to bring in dynamic variables as well as additional static variables to better represent landslide hazard globally. Global rainfall forecasts are also being evaluated to provide a 1-3 day forecast of potential landslide activity. Additional factors such as recent seismicity and burned areas are also being considered to represent the preconditioning or changing interactions with subsequent rainfall over affected areas. A series of parameters are being tested within this structure using NASA’s Global Landslide Catalog as well as many other event-based and multi-temporal inventories mapped by the project team or provided by project partners. In addition to estimates of landslide hazard, LHASA Version 2 will incorporate dynamic estimates of exposure including population, roads and infrastructure to highlight the potential impacts that rainfall-triggered landslides. The ultimate goal of LHASA Version 2.0 is to approximate the relative probabilities of landslide hazard and exposure across different space and time scales to inform hazard assessment retrospectively over the past 20 years, in near real-time, and in the future. In addition to the hazard. This presentation will outline the new activities for LHASA Version 2.0 and present some next steps for this system.
An inspection of 34 SRC/ESO J southern sky fields is the basis of the present list of clusters of galaxies and their approximate classifications in terms of cluster concentration, defined independently of richness and shape-symmetry. Where possible, an estimate of the cluster morphological population is provided. The Bautz-Morgan classification was applied using a strict comparison with clusters on the Palomar Sky Survey. Magnitudes were estimated on the basis of galaxies with photoelectric or photographic magnitudes.
Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidence of renal stones in US astronauts exists and the question "How much does this risk change with space flight?" remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone presentation. The modeling process utilizes a Population Balance Equation based model developed in the companion IWS abstract by Kassemi et al. (2016) to evaluate the maximum growth and agglomeration potential from a specified set of urine chemistry values. Changes in renal stone occurrence rates are obtained from this model in a probabilistic simulation that interrogates the range of possible urine chemistries using Monte Carlo techniques. Subsequently, each randomly sampled urine chemistry undergoes speciation analysis using the well-established Joint Expert Speciation System (JESS) code to calculate critical values, such as ionic strength and relative supersaturation. The Kassemi model utilizes this information to predict the mean and maximum stone size. We close the assessment loop by using a transfer function that estimates the rate of stone formation from combining the relative supersaturation and both the mean and maximum free stone growth sizes. The transfer function is established by a simulation analysis which combines population stone formation rates and Poisson regression. Training this transfer function requires using the output of the aforementioned assessment steps with inputs from known non-stone-former and known stone-former urine chemistries. Established in a Monte Carlo system, the entire renal stone analysis model produces a probability distribution of the stone formation rate and an expected uncertainty in the estimate. The utility of this analysis will be demonstrated by showing the change in renal stone occurrence predicted by this method using urine chemistry distributions published in Whitson et al. 2009. A comparison to the model predictions to previous assessments of renal stone risk will be used to illustrate initial validation of the model.
The problem of radiation exposure of crewmembers in high altitude supersonic commercial aircraft is addressed. As a result of recent changes in the quality factors for radiological protection, it is found that worst case estimates of radiation exposure are now well above the exposure limits of the general population, and a reassessment of radiation impact on commercial aviation is needed, if the proposed quality factors are adopted. Calculations are presented from a study on neutron dosage equivalent rates. It is shown that a crew flying at altitudes near 13 km (43,000 ft) for 40 hr/mo would receive exposure levels of 47-75 Sv/yr, and it is suggested that such crewmembers be considered as radiation workers, rather than general population members. However, since present exposure estimates need to be improved, and the maximum permissible dose limits are currently under revision, the final exposure limits are, as yet, unclear, suggesting the need for further study to clarify the work status of commercial aircrews.
Recent impact crater counts on the Voyager 2 high resolution images of Triton have resulted in a more accurate crater size/frequency distribution down to about 3 km diameter. These counts reveal a size/frequency distribution characterized by a differential -4 slope. This is consistent with the observation that there are no craters larger than 27 km diameter on the 20 percent of Triton viewed at resolutions capable of detecting them. A -4 slope is deficient in large craters and at the very low crater density on Triton no craters larger than about 30 km are expected on just 20 percent of the satellite. The Triton size distribution is significantly different from the differential -3 slope of the fresh crater population on Miranda, but both show leading/trailing asymmetries. Since Miranda is in prograde orbit this crater population is probably due to objects in heliocentric orbit, i.e., comets. If this crater population is due to comets, then the significantly different crater population on Triton is probably due to some other population of impacting objects. The most likely origin of these objects is planetesimals in planetocentric orbits. Because Triton is in retrograde orbit, objects in prograde planetocentric orbits will also produce a leading/trailing asymmetry. If the Triton craters are largely the result of objects in planetocentric orbit, then where are the comet craters that should be there if they have a differential -3 distribution function as inferred from the Miranda fresh crater population? The most likely answer is that they are there, but at such a low density that they can not be distinguished from the planetocentric population. An upper bound on this density can be estimated by determining the density of a crater population with a differential -3 slope where no craters larger than 27 km would be expected on the 20 percent of Triton viewed by Voyager at resolutions sufficient to detect them. This density is at the density of the largest crater. At this density the number of craters in size bins greater than 27 km is less than 1 for a -3 distribution function. The observed size distribution, the upper limit of the hypothetical comet crater size distribution, and the difference between the observed and the hypothetical comet crater populations is shown.
The twenty-first century is the first urban century according to the United Nations Development Program. The focus on cities reflects awareness of the growing percentage of the world's population that lives in urban areas. In 2000, approximately 3 billion people representing about 40% of the global population resided in urban areas. The United Nations estimates that by 2025, 60% of the world s population will live in urban areas. As a consequence, the number of megacities (those cities with populations of 10 million inhabitants or more) will increase by 100 by 2025. Thus, there is a critical need to understand the spatial growth of urban areas and what the impacts are on the environment. Moreover, there is a critical need to assess how under global climate change, cities will affect the local, regional, and even global climate. As urban areas increase in size, it is anticipated there will be a concomitant growth of the Urban Heat Island effect (UHI), and the attributes that are related to its spatial and temporal dynamics. Therefore, how climate change, including the dynamics of the UHI, will affect the urban environment, must be explored to help mitigate potential impacts on the environment (e.g., air quality, heat stress, vectorborne disease) and on human health and well being, to develop adaptation schemes to cope with these impacts.
Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.
Spacecraft surfaces that are destined to land on potential life-harboring celestial bodies are required to be rigorously cleaned and continuously monitored for spore bioburden as a proxy for spacecraft cleanliness. The NASA standard spore assay (NSA), used for spacecraft bioburden estimates, specifically measures spores that are cultivable, aerobic, resistant to heat shock, and grow at 30˚C in a nutrient-rich medium. Since the vast majority of microorganisms cannot be cultivated using the NSA assay, it is necessary to utilize state-of-the art molecular techniques to better understand the presence of all viable microorganisms, not just those measured with the NSA. In this study, the nutrient-deprived low biomass cleanrooms, where spacecraft are assembled, were used as a surrogate to spacecraft surfaces to measure the ratio of NSA spores in relation to the total viable microorganism population to compare with a 2006 space studies report that estimates that for every 1 spore there is approximately 50,000 viable organisms. Ninety-eight surface wipe samples were collected from the spacecraft assembly facility (SAF) cleanroom at the Jet Propulsion Laboratory (JPL) over a 6-month period. The samples were processed and analyzed using classical microbiology along with molecular assays. Traditional microbiology plating methods were used to determine the cultivable bacterial, fungal, and spore populations. Molecular assays were used to determine the total organisms (TO, dead and live) and the viable organisms (VO, live). The TO was measured using adenine triphosphate (ATP) and quantitative polymerase chain reaction (qPCR) assays. The VO was measured using internal ATP, propidium monoazide (PMA)-qPCR, and flow cytometry (after staining for viable microorganisms) assays. Based on the results, it was possible to establish a ratio between spore counts and VO for each viability assay. The ATP based spore to VO ratio ranged from 149 – 746 and the bacterial PMA-qPCR assay based ratio ranged from 314 – 1491 VO. The most conservative estimate came from FACS, which estimated the ratio to be 12,091 VO per 1 NSA spore. Since archaeal (<1%) and fungal (~2%) populations were negligible, the spore to VO ratios were based on bacterial population estimates. The most conservative ratio from this study can be used as a replacement for the SSB estimate on nutrient-deprived (oligotrophic) desiccated spacecraft surfaces, to estimate the VO from NSA measurements without utilizing state-of-the art molecular methods that are costly and require more biomass than is typically found of spacecraft surfaces.
The goal of this session is to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results focusing on the impact of urbanization on the climate. The discussion will highlight current observational and modeling capabilities being employed for investigating the urban environment and its linkage to the change in the Earth's climate system. The goal of the session is to identify our current stand and the future direction on the topic. Urbanization is one of the extreme cases of land use change. Most of population of the world has moved to urban areas. By 1995, more than 70% of population of North America and Europe were living in cities. By 2025, the United Nations estimates that 60% of the worlds population will live in cities. Although currently only 1.2% of the land is urban, better understanding of how the atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of human activities on this system is critical. Our understanding of urbanization effect is incomplete, partly because human activities induce new changes on climate in addition to the original natural variations, and partly because previously few data available for study urban effect globally. Urban construction changes surface roughness, albedo, heat capacity and vegetation coverage. Traffic and industry increase atmospheric aerosol. It is suggested that urbanization may modify rainfall processes through aerosol-cloud interactions or dynamic feedbacks. Because urbanization effect on climate is determined by many factors including land cover, the city's microscale features, population density, and human lifestyle patterns, it is necessary to study urban areas over globe.
We present observations of the Auriga-California Molecular Cloud (AMC) at 3.6, 4.5, 5.8, 8.0, 24, 70 and 160 micrometers observed with the IRAC and MIPS detectors as part of the Spitzer Gould Belt Legacy Survey. The total mapped areas are 2.5 deg(exp 2) with IRAC and 10.47 deg2 with MIPS. This giant molecular cloud is one of two in the nearby Gould Belt of star-forming regions, the other being the Orion A Molecular Cloud (OMC). We compare source counts, colors and magnitudes in our observed region to a subset of the SWIRE data that was processed through our pipeline. Using color-magnitude and color-color diagrams, we find evidence for a substantial population of 166 young stellar objects (YSOs) in the cloud, many of which were previously unknown. Most of this population is concentrated around the LkH(alpha) 101 cluster and the filament extending from it. We present a quantitative description of the degree of clustering and discuss the fraction of YSOs in the region with disks relative to an estimate of the diskless YSO population. Although the AMC is similar in mass, size and distance to the OMC, it is forming about 15 - 20 times fewer stars.
Data from a nationally representative survey of time use was analyzed to provide estimates of the percentage of the population which is engaged in noise sensitive activities during each hour of the day on weekdays, Fridays, Saturdays and Sundays. Estimates are provided of the percentage engaged in aural communication activities at home, sleeping at home, or simply at home. The day can be roughly divided into four noise sensitivity periods consisting of two relatively steady state periods, night and day and the early morning and evening transition periods. Weekends differ from weekdays in that the morning transition period is one hour later and the numbers of people engaged in aural communication during the day at home are approximately one-half to three-quarters greater. The extent and timing of noise sensitive activities was found to be similiar for all parts of the United States, for different sizes of urban areas, and for the three seasons surveyed (September through May). The timing of activity periods does not differ greatly by sex or age even though women and people over 65 are much more likely to be at home during the daytime.
Routine lunar impact monitoring has harvested over 110 impacts in 2 years of observations using 0.25, 0.36 and 0.5 m telescopes and low-light-level video cameras. The night side of the lunar surface provides a large collecting area for detecting these impacts and allows estimation of the flux of meteoroids down to a limiting luminous energy. In order to determine the limiting mass for these observations, models of the sporadic meteoroid environment were used to determine the velocity distribution and new measurements of luminous efficiency were made at the Ames Vertical Gun Range. The flux of meteoroids in this size range has implications for Near Earth Object populations as well as for estimating impact ejecta risk for future lunar missions.
The H2 emission from the Orion Molecular Cloud is, by an order of magnitude, the brightest known example of H2 emission, offering a means by which to estimate quantities connected with the mass flow. The size, temperature, velocity, and intensity of the lines can be used to infer the mass loss rate, the rate at which momentum is yielded to the cloud through masss loss, and the energy dissipation rate as the cloud is disrupted internally. Attention is accordingly given to the most recent observational results, with respect to morphology, extinction, level populations, and excitation temperature. The estimates concerning the mass loss phenomenon derived from H2 observations yield approximately the same numbers of those inferred from CO and H2O maser observations.
Examples (1-D seismic, large flexible structures, bioturbation, nonlinear population dispersal) in which a variation setting can provide a convenient framework for convergence and stability arguments in parameter estimation problems are considered. Some of these examples are 1-D seismic, large flexible structures, bioturbation, and nonlinear population dispersal. Arguments for convergence and stability via a variational approach of least squares formulations of parameter estimation problems for partial differential equations is one aspect of the problem considered.