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1.
Space Sci Rev ; 216(1): 12, 2020.
Article in English | MEDLINE | ID: mdl-32025061

ABSTRACT

The OSIRIS-REx Camera Suite (OCAMS) onboard the OSIRIS-REx spacecraft is used to study the shape and surface of the mission's target, asteroid (101955) Bennu, in support of the selection of a sampling site. We present calibration methods and results for the three OCAMS cameras-MapCam, PolyCam, and SamCam-using data from pre-flight and in-flight calibration campaigns. Pre-flight calibrations established a baseline for a variety of camera properties, including bias and dark behavior, flat fields, stray light, and radiometric calibration. In-flight activities updated these calibrations where possible, allowing us to confidently measure Bennu's surface. Accurate calibration is critical not only for establishing a global understanding of Bennu, but also for enabling analyses of potential sampling locations and for providing scientific context for the returned sample.

2.
Health Care Financ Rev ; 14(2): 31-47, 1992.
Article in English | MEDLINE | ID: mdl-10127452

ABSTRACT

The elimination of urban-rural differences in the Medicare prospective payment system (PPS) standard rates implies a need to re-examine all the PPS payment adjustments. Refinements for case mix, outliers, and the wage index can make a significant contribution to avoiding payment disparities in a single-rate system. However, changes in the adjustments for teaching and disproportionate-share (DSH) hospitals are also needed. The typically urban location of these hospitals makes it difficult to balance PPS payments and costs among major groups of urban and rural hospitals without some form of higher payment for all hospitals located in large urban areas.


Subject(s)
Hospitals, Rural/economics , Hospitals, Urban/economics , Medicare Part A/economics , Prospective Payment System/standards , Diagnosis-Related Groups/economics , Hospitals, Teaching/economics , Medicare Part A/statistics & numerical data , Outliers, DRG/economics , Rate Setting and Review/standards , Regression Analysis , United States
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