Apollo experience report: Guidance and control systems: CSM service propulsion system gimbal actuators

The service propulsion system gimbal actuators of the Apollo command and service module were developed, modified, and qualified between February 1962 and April 1968. The development of these actuators is described as the result of extensive testing, retesting, and modification of the initial design. Successful completion of each mission without anomalies attributable to the actuators indicated that the particular configuration (modification) in use was adequate for the flight profile imposed

Developing a Pan-European Approach to Teacher Educators

This paper explores from an English perspective the outcomes of the InFo-TED* Summer Academy: a pan- European attempt to encourage collaboration in professional development for teacher educators (see Conway et al., 2015; Czerniawski et al., 2017). In exploring the experience and outcomes of collaborative professional development through the InFo-TED project, we recognise that the diversity of teacher education routes in England and shifting policy landscapes (Murray et al., 2017) create salient opportunities to explore the English context in line with European policy directives (Czerniawski et al., 2018; Vanassche et al., 2019) and the enacted and lived professional experiences of other European colleagues in this shifting field. To do this, this paper draws upon the auto-ethnographical reflections, vignettes and journals of Summer Academy participants, seeking to situate teacher educators’ practices within the ‘concrete context’ of teacher education reform (Vanassche et al., 2015). Within this context, we argue, is the need for a returned attention to teacher educators’ development

The external benefits of higher education

The private market benefits of education are widely studied at the micro level, although the magnitude of their macroeconomic impact is disputed. However, there are additional benefits of education, which are less well understood. In this paper the macroeconomic effects of external benefits of higher education are estimated using the “micro-to-macro” simulation approach. Two types of externalities are explored: technology spillovers and productivity spillovers in the labour market. These links are illustrated and the results suggest they could be very large. However, this is qualified by the dearth of microeconomic evidence, for which we hope to encourage further work

Impact of Fuel Price Increases on Texas Crops

Replaced with revised version of paper 02/02/06.crop model, simulation, input-output model, Resource /Energy Economics and Policy, C53, Q10,

PMN J0525-3343: soft X-ray spectral flattening in a blazar at z=4.4

We report optical, radio and X-ray observations of a new distant blazar, PMN J0525-3343, at a redshift of 4.4. The X-ray spectrum measured from ASCA and BeppoSAX flattens below a few keV, in a manner similar to the spectra of two other z>4 blazars, GB 1428+4217 (z=4.72) reported by Boller et al and RXJ 1028.6-0844 (z=4.28) by Yuan et al. The spectrum is well fitted by a power-law continuum which is either absorbed or breaks at a few keV. An intrinsic column density corresponding to 2 x 10^23 H-atoms cm-2 at solar abundance is required by the absorption model. This is however a million times greater than the neutral hydrogen, or dust, column density implied by the optical spectrum, which covers the rest-frame UV emission of the blazar nucleus. We discuss the problems raised and suggest that, unless there is intrinsic flattening in the spectral distribution of the particles/seed photons producing X-rays via inverse Compton scattering, the most plausible solution is a warm absorber close to the active nucleus.Comment: 7 pages, 7 figures; MNRAS, in pres

Density Estimation for Entry Guidance Problems using Deep Learning

This work presents a deep-learning approach to estimate atmospheric density profiles for use in planetary entry guidance problems. A long short-term memory (LSTM) neural network is trained to learn the mapping between measurements available onboard an entry vehicle and the density profile through which it is flying. Measurements include the spherical state representation, Cartesian sensed acceleration components, and a surface-pressure measurement. Training data for the network is initially generated by performing a Monte Carlo analysis of an entry mission at Mars using the fully numerical predictor-corrector guidance (FNPEG) algorithm that utilizes an exponential density model, while the truth density profiles are sampled from MarsGRAM. A curriculum learning procedure is developed to refine the LSTM network's predictions for integration within the FNPEG algorithm. The trained LSTM is capable of both predicting the density profile through which the vehicle will fly and reconstructing the density profile through which it has already flown. The performance of the FNPEG algorithm is assessed for three different density estimation techniques: an exponential model, an exponential model augmented with a first-order fading-memory filter, and the LSTM network. Results demonstrate that using the LSTM model results in superior terminal accuracy compared to the other two techniques when considering both noisy and noiseless measurements.Comment: Currently under revision for the AIAA Journal of Guidance Control and Dynamic