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- Herique, A., et al.
(författare)
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Direct observations of asteroid interior and regolith structure : Science measurement requirements
- 2018
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Ingår i: Advances in Space Research. - : Elsevier BV. - 0273-1177 .- 1879-1948. ; 62:8, s. 2141-2162
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Tidskriftsartikel (refereegranskat)abstract
- Our knowledge of the internal structure of asteroids is, so far, indirect - relying entirely on inferences from remote sensing observations of the surface, and theoretical modeling of formation and evolution. What are the bulk properties of the regolith and deep interior? And what are the physical processes that shape asteroid internal structures? Is the composition and size distribution observed on the surface representative of the bulk? These questions are crucial to understand small bodies' history from accretion in the early Solar System to the present, and direct measurements are needed to answer these questions for the benefit of science as well as for planetary defense or exploration. Radar is one of the main instruments capable of sounding asteroids to characterize internal structure from sub-meter to global scale. In this paper, we review the science case for direct observation of the deep internal structure and regolith of a rocky asteroid of kilometer size or smaller. We establish the requirements and model dielectric properties of asteroids to outline a possible instrument suite, and highlight the capabilities of radar instrumentation to achieve these observations. We then review the expected science return including secondary objectives contributing to the determination of the gravitational field, the shape model, and the dynamical state. This work is largely inherited from MarcoPolo-R and AIDA/AIM studies.
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| 2. |
- Caly, H., et al.
(författare)
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Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD
- 2021
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- To identify newborns at risk of developing ASD and to detect ASD biomarkers early after birth, we compared retrospectively ultrasound and biological measurements of babies diagnosed later with ASD or neurotypical (NT) that are collected routinely during pregnancy and birth. We used a supervised machine learning algorithm with a cross-validation technique to classify NT and ASD babies and performed various statistical tests. With a minimization of the false positive rate, 96% of NT and 41% of ASD babies were identified with a positive predictive value of 77%. We identified the following biomarkers related to ASD: sex, maternal familial history of auto-immune diseases, maternal immunization to CMV, IgG CMV level, timing of fetal rotation on head, femur length in the 3rd trimester, white blood cell count in the 3rd trimester, fetal heart rate during labor, newborn feeding and temperature difference between birth and one day after. Furthermore, statistical models revealed that a subpopulation of 38% of babies at risk of ASD had significantly larger fetal head circumference than age-matched NT ones, suggesting an in utero origin of the reported bigger brains of toddlers with ASD. Our results suggest that pregnancy follow-up measurements might provide an early prognosis of ASD enabling pre-symptomatic behavioral interventions to attenuate efficiently ASD developmental sequels.
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