High-fidelity landing simulation of small body landers: Modeling and mass distribution effects on bouncing motion

The gravity field of a small body provides insight into its internal mass distribution. We used two approaches to measure the gravity field of the rubble-pile asteroid (101955) Bennu: (i) tracking and modeling the spacecraft in orbit about the asteroid and (ii) tracking and modeling pebble-sized particles naturally ejected from Bennu’s surface into sustained orbits. These approaches yield statistically consistent results up to degree and order 3, with the particle-based field being statistically significant up to degree and order 9. Comparisons with a constant-density shape model show that Bennu has a heterogeneous mass distribution. These deviations can be modeled with lower densities at Bennu’s equatorial bulge and center. The lower-density equator is consistent with recent migration and redistribution of material. The lower-density center is consistent with a past period of rapid rotation, either from a previous Yarkovsky-O’Keefe-Radzievskii-Paddack cycle or arising during Bennu’s accretion following the disruption of its parent body.

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Analysis of STEM micrographs of thick objects

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100081395 ◽

1978 ◽

Vol 36 (2) ◽

pp. 106-107

Author(s):

S. Golladay

Keyword(s):

Inelastic Scattering ◽

Multiple Scattering ◽

Mass Distribution ◽

Cross Sections ◽

Phase Contrast ◽

Image Point ◽

Contrast Effects ◽

Total Cross Sections ◽

Elastic And Inelastic Scattering

The theory of multiple scattering has been worked out by Groves and comparisons have been made between predicted and observed signals for thick specimens observed in a STEM under conditions where phase contrast effects are unimportant. Independent measurements of the collection efficiencies of the two STEM detectors, calculations of the ratio σe/σi = R, where σe, σi are the total cross sections for elastic and inelastic scattering respectively, and a model of the unknown mass distribution are needed for these comparisons. In this paper an extension of this work will be described which allows the determination of the required efficiencies, R, and the unknown mass distribution from the data without additional measurements or models. Essential to the analysis is the fact that in a STEM two or more signal measurements can be made simultaneously at each image point.

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Using the Theory of Planned Behavior to Predict Faking in Selection Exercises Varying in Fidelity

Journal of Personnel Psychology ◽

10.1027/1866-5888/a000211 ◽

2018 ◽

Vol 17 (3) ◽

pp. 155-160 ◽

Cited By ~ 3

Author(s):

Daniel Dürr ◽

Ute-Christine Klehe

Keyword(s):

Theory Of Planned Behavior ◽

Planned Behavior ◽

Predictive Validity ◽

Group Discussion ◽

Role Play ◽

Selection Procedure ◽

High Fidelity ◽

Selection Research ◽

Play Group

Abstract. Faking has been a concern in selection research for many years. Many studies have examined faking in questionnaires while far less is known about faking in selection exercises with higher fidelity. This study applies the theory of planned behavior (TPB; Ajzen, 1991 ) to low- (interviews) and high-fidelity (role play, group discussion) exercises, testing whether the TPB predicts reported faking behavior. Data from a mock selection procedure suggests that candidates do report to fake in low- and high-fidelity exercises. Additionally, the TPB showed good predictive validity for faking in a low-fidelity exercise, yet not for faking in high-fidelity exercises.

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The Impact of Missing and Error-Prone Auxiliary Information on Sparse-Matrix Sub-Population Parameter Estimates

Methodology ◽

10.1027/1614-2241/a000095 ◽

2015 ◽

Vol 11 (3) ◽

pp. 89-99 ◽

Cited By ~ 1

Author(s):

Leslie Rutkowski ◽

Yan Zhou

Keyword(s):

Sparse Matrix ◽

Small Body ◽

Auxiliary Information ◽

Poor Quality ◽

Quality Data ◽

Estimation Methods ◽

Parameter Estimates ◽

Population Parameter ◽

Conditioning Model ◽

The Impact

Abstract. Given a consistent interest in comparing achievement across sub-populations in international assessments such as TIMSS, PIRLS, and PISA, it is critical that sub-population achievement is estimated reliably and with sufficient precision. As such, we systematically examine the limitations to current estimation methods used by these programs. Using a simulation study along with empirical results from the 2007 cycle of TIMSS, we show that a combination of missing and misclassified data in the conditioning model induces biases in sub-population achievement estimates, the magnitude and degree to which can be readily explained by data quality. Importantly, estimated biases in sub-population achievement are limited to the conditioning variable with poor-quality data while other sub-population achievement estimates are unaffected. Findings are generally in line with theory on missing and error-prone covariates. The current research adds to a small body of literature that has noted some of the limitations to sub-population estimation.

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