저작근 근전도에 관한 정상교합자와 ii급 부정교합자의 비교 연구

Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariate data and the comparative lack of parametric models to represent it. Unfortunately, such exploration is also inherently more difficult.

Multivariate Density Estimation

During its approach to asteroid (101955) Bennu, NASA’s Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) spacecraft surveyed Bennu’s immediate environment, photometric properties, and rotation state. Discovery of a dusty environment, a natural satellite, or unexpected asteroid characteristics would have had consequences for the mission’s safety and observation strategy. Here we show that spacecraft observations during this period were highly sensitive to satellites (sub-meter scale) but reveal none, although later navigational images indicate that further investigation is needed. We constrain average dust production in September 2018 from Bennu’s surface to an upper limit of 150 g s–1 averaged over 34 min. Bennu’s disk-integrated photometric phase function validates measurements from the pre-encounter astronomical campaign. We demonstrate that Bennu’s rotation rate is accelerating continuously at 3.63 ± 0.52 × 10–6 degrees day–2, likely due to the Yarkovsky–O’Keefe–Radzievskii–Paddack (YORP) effect, with evolutionary implications.

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The operational environment and rotational acceleration of asteroid (101955) Bennu from OSIRIS-REx observations

High-resolution gravity data obtained from the dual Gravity Recovery and Interior Laboratory (GRAIL) spacecraft show that the bulk density of the Moon's highlands crust is 2550 kilograms per cubic meter, substantially lower than generally assumed. When combined with remote sensing and sample data, this density implies an average crustal porosity of 12% to depths of at least a few kilometers. Lateral variations in crustal porosity correlate with the largest impact basins, whereas lateral variations in crustal density correlate with crustal composition. The low-bulk crustal density allows construction of a global crustal thickness model that satisfies the Apollo seismic constraints, and with an average crustal thickness between 34 and 43 kilometers, the bulk refractory element composition of the Moon is not required to be enriched with respect to that of Earth.

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The Crust of the Moon as Seen by GRAIL

Lunar sourcebook. A user's guide to the moon

The moon of the near-Earth binary asteroid 65803 Didymos is the target of the Asteroid Impact and Deflection Assessment (AIDA) mission. This mission is a joint concept between NASA and ESA to investigate the effectiveness of a kinetic impactor in deflecting an asteroid. The mission is com- posed of two components: the NASA-led Double As- teroid Redirect Test (DART) that will impact the Did- ymos moon (henceforth Didymoon), and the ESA-led Asteroid Impact Mission (AIM) that will survey the Didymos system. Using much of ESA’s Rosetta experience, the AIM mission will undertake all the proximity operations both before and after the impact produced by DART. The physical and dynamical characterization of both Didymain (primary) and Didymoon is of maximum importance in the joint AIDA mission and the main purpose of the AIM spacecraft. The characterization includes measuring before and after the 
DART impact, the internal properties of the primary and secondary, the mass of Didymoon, the surface geology and regolith properties of both objects, and the dynamical state of Didymoon [1]. In this abstract, we summarize the proximity operations needed to achieve the scientific 
objectives of the AIM spacecraft using the broad suite of experiments it will carry to satisfy its mission objectives.

The Asteroid Impact and Deflection Assessment (AIDA) Mission: Science Proximity Operations

We present a regional photometric analysis of asteroid (101955) Bennu, using image data from the MapCam color imager of the OSIRIS-REx Camera Suite (OCAMS). This analysis follows the previously reported global photometric analysis of Bennu, which found that Bennu’s roughness was difficult to photometrically model owing to unresolved surface variation. Here we find that, even with a high-resolution shape model (20 cm per facet) and automatic image registration (<1 pixel error), Bennu remains a challenging surface to photometrically model: neither a suite of empirical photometric models nor the physically motivated Hapke model were able to eliminate the scatter in the data due to pixel-scale variations. Nonetheless, the models improved on the global analysis by identifying regional variations in Bennu’s photometric response. A linear empirical model, when compared with independent measures of surface roughness and albedo, revealed correlations between those characteristics and phase slope. A regional Hapke analysis showed the same structure in its single-scattering albedo and asymmetry factors; although the Hapke parameters were loosely constrained, complicating interpretation of their spatial variation, the regional variation in relative parameter sensitivity also correlated with shallower phase slope, higher albedo, and less macroscopic roughness.

Regional Photometric Modeling of Asteroid (101955) Bennu

On the possible origin of terraces on Bennu

Could the Hokusai Impact Have Delivered Mercury's Water Ice?

Introduction: Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer will use Stereophotoclinometry [1] (SPC) to generate the shape model of its target, Bennu. This shape model will be used to aid navigation and science processing [2]. The Altimetry Working Group has conducted numerous tests to evaluate the accuracy and performance of SPC in preparation for mission operations when OSIRIS-REx arrives at Bennu. The testing used several truth models that simulated both substantially rough and less rough shape objects with surface albedo, and also included navigational errors to identify SPC's robustness to meet the OSIRIS-REx accuracy requirements [3]. The main metric for the quality of a shape model is to subtract the generated model from the truth model (from which the simulated images were generated), and calculate the root mean squared differences of every vertex (RMS). Subtracting two models is the main tool that is typically used to evaluate two different shape models, such as what was done for Vesta [4]. For a global model, especially one built with direct measurement such as a laser altimeter, it provides a strong measurement of the model.

Olivier S. Barnouin

Papers

The Asteroid Impact and Deflection Assessment (AIDA) Mission: Science Proximity Operations

Regional Photometric Modeling of Asteroid (101955) Bennu

On the possible origin of terraces on Bennu

Could the Hokusai Impact Have Delivered Mercury's Water Ice?

Image Cross Correlation as a Measurement of Shape Model Quality