Mission and spacecraft support functions of the Materials Engineering Branch: A space oriented technology resource

The capabilities of the Materials Engineering Branch (MEB) of the Goddard Space Flight Center, Greenbelt, Maryland, are surveyed. The specific functions of spacecraft materials review, materials processing and information dissemination, and laboratory support, are outlined in the Activity Report. Further detail is provided by case histories of laboratory satellite support and equipment. Project support statistics are shown, and complete listings of MEB publications, patents, and tech briefs are included. MEB staff, and their respective discipline areas and spacecraft liaison associations, are listed

Proxying ability by family background in returns to schooling estimations is generally a bad idea

A regression model is considered where earnings are explained by schooling and ability. It is assumed that schooling is measured with error and that there are no data on ability. Regressing earnings on observed schooling then yields an estimate of the return to schooling that is subject to positive omitted variable bias (OVB) and negative measurement error bias (MEB). The effects on the OVB and the MEB from using family background variables as proxies for ability are investigated theoretically and empirically. The theoretical analysis demonstrates that the impact on the OVB is uncertain, while the MEB invariably increases in magnitude. The empirical analysis shows that the MEB generally dominates the OVB. As the measurement error increases and/or more family background variables are added, the total bias rapidly becomes negative, driving the estimated return further and further away from the true value.Missing data; proxy variables; measurement error; consistent estimates of omitted variable bias and measurement error bias

A multi-exit recirculating optical packet buffer

We propose a new type of recirculating buffer, the multiexit buffer (MEB), for use in asynchronous optical packet switches with statistical multiplexing, operating at speeds of 40-100 Gb/s. We demonstrate that the use of this type of buffer dramatically reduces the packet loss for a given buffer depth, thus reducing the buffer depth requirements and the overall cost of the optical packet switching. Physical layer simulation results show that it is possible to build this type of buffer with currently available active components. A hybrid optoelectronic control system is proposed, which allows control of the MEB with a minimum number of active components

Producing Distant Planets by Mutual Scattering of Planetary Embryos

It is likely that multiple bodies with masses between those of Mars and Earth ("planetary embryos") formed in the outer planetesimal disk of the solar system. Some of these were likely scattered by the giant planets into orbits with semi-major axes of hundreds of AU. Mutual torques between these embryos may lift the perihelia of some of them beyond the orbit of Neptune, where they are no longer perturbed by the giant planets so their semi-major axes are frozen in place. We conduct N-body simulations of this process, and its effect on smaller planetesimals in the region of the giant planets and the Kuiper belt. We find that (i) there is a significant possibility that one sub-Earth mass embryo, or possibly more, is still present in the outer solar system; (ii) the orbit of the surviving embryo(s) typically has perihelion of 40--70 AU, semi-major axis less than 200 AU, and inclination less than 30 degrees; (iii) it is likely that any surviving embryos could be detected by current or planned optical surveys or have a significant effect on solar-system ephemerides; (iv) whether or not an embryo has survived to the present day, their dynamical influence earlier in the history of the solar system can explain the properties of the detached disk (defined in this paper as containing objects with perihelia > 38 AU and semi-major axes between 80 and 500 AU).Comment: Accepted to A.

A New Low-Mass Eclipsing Binary from SDSS-II

We present observations of a new low-mass double-lined eclipsing binary system discovered using repeat observations of the celestial equator from the Sloan Digital Sky Survey II. Using near-infrared photometry and optical spectroscopy we have measured the properties of this short-period [P=0.407037(14) d] system and its two components. We find the following parameters for the two components: M_1=0.272+/-0.020 M_sun, R_1=0.268+/-0.010 R_sun, M_2=0.240+/-0.022 M_sun, R_2=0.248+/-0.0090 R_sun, T_1=3320+/-130 K, T_2=3300+/-130 K. The masses and radii of the two components of this system agree well with theoretical expectations based on models of low-mass stars, within the admittedly large errors. Future synoptic surveys like Pan-STARRS and LSST will produce a wealth of information about low-mass eclipsing systems and should make it possible, with an increased reliance on follow-up observations, to detect many systems with low-mass and sub-stellar companions. With the large numbers of objects for which these surveys will produce high-quality photometry, we suggest that it becomes possible to identify such systems even with sparse time sampling and a relatively small number of individual observations.Comment: 15 Pages, 9 Figures, 6 Tables. Replaced with version accepted to Ap

Training Support Vector Machines Using Frank-Wolfe Optimization Methods

Training a Support Vector Machine (SVM) requires the solution of a quadratic programming problem (QP) whose computational complexity becomes prohibitively expensive for large scale datasets. Traditional optimization methods cannot be directly applied in these cases, mainly due to memory restrictions. By adopting a slightly different objective function and under mild conditions on the kernel used within the model, efficient algorithms to train SVMs have been devised under the name of Core Vector Machines (CVMs). This framework exploits the equivalence of the resulting learning problem with the task of building a Minimal Enclosing Ball (MEB) problem in a feature space, where data is implicitly embedded by a kernel function. In this paper, we improve on the CVM approach by proposing two novel methods to build SVMs based on the Frank-Wolfe algorithm, recently revisited as a fast method to approximate the solution of a MEB problem. In contrast to CVMs, our algorithms do not require to compute the solutions of a sequence of increasingly complex QPs and are defined by using only analytic optimization steps. Experiments on a large collection of datasets show that our methods scale better than CVMs in most cases, sometimes at the price of a slightly lower accuracy. As CVMs, the proposed methods can be easily extended to machine learning problems other than binary classification. However, effective classifiers are also obtained using kernels which do not satisfy the condition required by CVMs and can thus be used for a wider set of problems