Development of a funding, cost, and spending model for satellite projects

The need for a predictive budget/funging model is obvious. The current models used by the Resource Analysis Office (RAO) are used to predict the total costs of satellite projects. An effort to extend the modeling capabilities from total budget analysis to total budget and budget outlays over time analysis was conducted. A statistical based and data driven methodology was used to derive and develop the model. Th budget data for the last 18 GSFC-sponsored satellite projects were analyzed and used to build a funding model which would describe the historical spending patterns. This raw data consisted of dollars spent in that specific year and their 1989 dollar equivalent. This data was converted to the standard format used by the RAO group and placed in a database. A simple statistical analysis was performed to calculate the gross statistics associated with project length and project cost ant the conditional statistics on project length and project cost. The modeling approach used is derived form the theory of embedded statistics which states that properly analyzed data will produce the underlying generating function. The process of funding large scale projects over extended periods of time is described by Life Cycle Cost Models (LCCM). The data was analyzed to find a model in the generic form of a LCCM. The model developed is based on a Weibull function whose parameters are found by both nonlinear optimization and nonlinear regression. In order to use this model it is necessary to transform the problem from a dollar/time space to a percentage of total budget/time space. This transformation is equivalent to moving to a probability space. By using the basic rules of probability, the validity of both the optimization and the regression steps are insured. This statistically significant model is then integrated and inverted. The resulting output represents a project schedule which relates the amount of money spent to the percentage of project completion

Some Explicit Solutions for a Class of One-Phase Stefan Problems

Salva and Tarzia, [N.N. Salva, D.A. Tarzia, J. Math. Anal. Appl. 379 (2011) 240 - 244], gave explicit solutions of a similarity type for a class of free boundary problem for a semi-infinite material. In this paper, through an elementary approach and less stringent assumption on data, we obtain more general results than those given by their central result, and thereby construct explicit solutions for a wider class of Stefan problems with a type of variable heat flux boundary conditions. Further, explicit solutions of certain forced one-phase Stefan problems are given

The ASAC Air Carrier Investment Model (Second Generation)

To meet its objective of assisting the U.S. aviation industry with the technological challenges of the future, NASA must identify research areas that have the greatest potential for improving the operation of the air transportation system. To accomplish this, NASA is building an Aviation System Analysis Capability (ASAC). The ASAC differs from previous NASA modeling efforts in that the economic behavior of buyers and sellers in the air transportation and aviation industries is central to its conception. To link the economics of flight with the technology of flight, ASAC requires a parametrically based mode with extensions that link airline operations and investments in aircraft with aircraft characteristics. This model also must provide a mechanism for incorporating air travel demand and profitability factors into the airlines' investment decisions. Finally, the model must be flexible and capable of being incorporated into a wide-ranging suite of economic and technical models that are envisioned for ASAC. We describe a second-generation Air Carrier Investment Model that meets these requirements. The enhanced model incorporates econometric results from the supply and demand curves faced by U.S.-scheduled passenger air carriers. It uses detailed information about their fleets in 1995 to make predictions about future aircraft purchases. It enables analysts with the ability to project revenue passenger-miles flown, airline industry employment, airline operating profit margins, numbers and types of aircraft in the fleet, and changes in aircraft manufacturing employment under various user-defined scenarios

Research Report: A Preliminary Analysis of Medical Futility Decisionmaking: Law and Professional Attitudes

The debate in medical futility decisionmaking centers on the conflict between a patient insisting treatment and a doctor refusing to furnish it. Courts have taken two disparate approaches to the legal status of medical futility. Believing that such legal ambiguity may reflect ambiguity in the medical profession itself, this research report sought to identify any emerging consensus among professionals handling medical futility issues. The report explains the results of the Life Sustaining Treatment Survey, a nationwide survey of health care professionals at hospitals. Presented with a list of criteria, respondents assigned important ratings to the factors used in recent futility decisions at their institutions. The resulting data suggests that there is no consensus among professionals in medical futility decisionmaking. The data supports at least three distinct approaches for making futility decisions: emphasis on the patients’ preferences; providing for the patient and family; and adhering to objective medical and social norms. It is unlikely that the law will realize its full potential to regulate futility judgments until explicitly articulated professional standards emerge. This article advocates continued empirical research to document and test professional judgment principles. Such research may ultimately help identify factors that will form the basis for a consensus in medical futility decisionmaking

Forecasting ward-level bed requirements to aid pandemic resource planning: Lessons learned and future directions

During the COVID-19 pandemic, there has been considerable research on how regional and country-level forecasting can be used to anticipate required hospital resources. We add to and build on this work by focusing on ward-level forecasting and planning tools for hospital staff during the pandemic. We present an assessment, validation, and deployment of a working prototype forecasting tool used within a modified Traffic Control Bundling (TCB) protocol for resource planning during the pandemic. We compare statistical and machine learning forecasting methods and their accuracy at one of the largest hospitals (Vancouver General Hospital) in Canada against a medium-sized hospital (St. Paul's Hospital) in Vancouver, Canada through the first three waves of the COVID-19 pandemic in the province of British Columbia. Our results confirm that traditional statistical and machine learning (ML) forecasting methods can provide valuable ward-level forecasting to aid in decision-making for pandemic resource planning. Using point forecasts with upper 95% prediction intervals, such forecasting methods would have provided better accuracy in anticipating required beds on COVID-19 hospital units than ward-level capacity decisions made by hospital staff. We have integrated our methodology into a publicly available online tool that operationalizes ward-level forecasting to aid with capacity planning decisions. Importantly, hospital staff can use this tool to translate forecasts into better patient care, less burnout, and improved planning for all hospital resources during pandemics

Modeling 5 Years of Subglacial Lake Activity in the MacAyeal Ice Stream (Antarctica) Catchment Through Assimilation of ICESat Laser Altimetry

Subglacial lakes beneath Antarctica’s fast-moving ice streams are known to undergo ~1km3 volume changes on annual timescales. Focusing on the MacAyeal Ice Stream (MacIS) lake system, we create a simple model for the response of subglacial water distribution to lake discharge events through assimilation of lake volume changes estimated from Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry. We construct a steady-state water transport model in which known subglacial lakes are treated as either sinks or sources depending on the ICESat-derived filling or drainingrates. The modeled volume change rates of five large subglacial lakes in the downstream portion of MacIS are shown to be consistent with observed filling rates if the dynamics of all upstream lakes are considered. However, the variable filling rate of the northernmost lake suggests the presence of an undetected lake of similar size upstream. Overall, we show that, for this fast-flowing ice stream, most subglacial lakes receive \u3e90% of their water from distant distributed sources throughout the catchment, and we confirm that water is transported from regions of net basal melt to regions of net basal freezing. Our study provides a geophysically based means of validating subglacial water models in Antarctica and is a potential way to parameterize subglacial lake discharge events in large-scale ice-sheet models where adequate data are available

A Diffuse Metal-Poor Component of the Sagittarius Stream Revealed by the H3 Survey

The tidal disruption of the Sagittarius dwarf galaxy has generated a spectacular stream of stars wrapping around the entire Galaxy. We use data from $Gaia$ and the H3 Stellar Spectroscopic Survey to identify 823 high-quality Sagittarius members based on their angular momenta. The H3 Survey is largely unbiased in metallicity, and so our sample of Sagittarius members is similarly unbiased. Stream stars span a wide range in [Fe/H] from $-0.2$ to $\approx -3.0$, with a mean overall metallicity of $\langle$[Fe/H]$\rangle=-0.99$. We identify a strong metallicity-dependence to the kinematics of the stream members. At [Fe/H]$\gt -0.8$ nearly all members belong to the well-known cold ($\sigma_v \lt 20$ km/s) leading and trailing arms. At intermediate metallicities ($-1.9 \lt$[Fe/H]$\lt -0.8$) a significant population (24$\%$) emerges of stars that are kinematically offset from the cold arms. These stars also appear to have hotter kinematics. At the lowest metallicities ([Fe/H]$\lesssim-2$), the majority of stars (69$\%$) belong to this kinematically-offset diffuse population. Comparison to simulations suggests that the diffuse component was stripped from the Sagittarius progenitor at earlier epochs, and therefore resided at larger radius on average, compared to the colder metal-rich component. We speculate that this kinematically diffuse, low metallicity, population is the stellar halo of the Sagittarius progenitor system.Comment: 18 pages, 12 figures, 1 table. Submitted to Ap

Discovery of the Magellanic Stellar Stream Out to 100 Kiloparsecs

The Magellanic Stream (MS) - an enormous ribbon of gas spanning $140^\circ$ of the southern sky trailing the Magellanic Clouds - has been exquisitely mapped in the five decades since its discovery. However, despite concerted efforts, no stellar counterpart to the MS has been conclusively identified. This stellar stream would reveal the distance and 6D kinematics of the MS, constraining its formation and the past orbital history of the Clouds. We have been conducting a spectroscopic survey of the most distant and luminous red giant stars in the Galactic outskirts. From this dataset, we have discovered a prominent population of 13 stars matching the extreme angular momentum of the Clouds, spanning up to $100^\circ$ along the MS at distances of $60-120$ kpc. Furthermore, these kinemetically-selected stars lie along a [$\alpha$/Fe]-deficient track in chemical space from $-2.5 < \mathrm{[Fe/H]} < -0.5$, consistent with their formation in the Clouds themselves. We identify these stars as high-confidence members of the Magellanic Stellar Stream. Half of these stars are metal-rich and closely follow the gaseous MS, whereas the other half are more scattered and metal-poor. We argue that the metal-rich stream is the recently-formed tidal counterpart to the MS, and speculate that the metal-poor population was thrown out of the SMC outskirts during an earlier interaction between the Clouds. The Magellanic Stellar Stream provides a strong set of constraints - distances, 6D kinematics, and birth locations - that will guide future simulations towards unveiling the detailed history of the Clouds.Comment: 21 pages, 12 figures. Submitted to Ap

Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value

Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 17 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (\u3e75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies