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The politics and perils of space exploration : who will compete, who will dominate?
\"Written by a former Aerodynamics Officer on the space shuttle program, this book provides a complete overview of the 'new' U.S. space program, which has changed considerably over the past 50 years. The future of space exploration has become increasingly dependent on other countries and private enterprise. Can private enterprise fill the shoes of NASA and provide the same expertise and safety measures and lessons learned from NASA? In order to tell this story, it is important to understand the politics of space as well as the dangers, why it is so difficult to explore and utilize the resources of space. Some past and recent triumphs and failures will be discussed, pointing the way to a successful space policy that includes taking risks but also learning how to mitigate them\"--Provided by publisher.
Book
We Could Not Fail
The Space Age began just as the struggle for civil rights forced Americans to confront the long and bitter legacy of slavery, discrimination, and violence against African Americans. Presidents John F. Kennedy and Lyndon Johnson utilized the space program as an agent for social change, using federal equal employment opportunity laws to open workplaces at NASA and NASA contractors to African Americans while creating thousands of research and technology jobs in the Deep South to ameliorate poverty. We Could Not Fail tells the inspiring, largely unknown story of how shooting for the stars helped to overcome segregation on earth. Richard Paul and Steven Moss profile ten pioneer African American space workers whose stories illustrate the role NASA and the space program played in promoting civil rights. They recount how these technicians, mathematicians, engineers, and an astronaut candidate surmounted barriers to move, in some cases literally, from the cotton fields to the launching pad. The authors vividly describe what it was like to be the sole African American in a NASA work group and how these brave and determined men also helped to transform Southern society by integrating colleges, patenting new inventions, holding elective office, and reviving and governing defunct towns. Adding new names to the roster of civil rights heroes and a new chapter to the story of space exploration, We Could Not Fail demonstrates how African Americans broke the color barrier by competing successfully at the highest level of American intellectual and technological achievement.
eBook
Hierarchical modeling strengthens evidence for density dependence in observational time series of population dynamics
The extent to which populations in nature are regulated by density-dependent processes is unresolved. While experiments increasingly find evidence of strong density dependence, unmanipulated population time series yield much more ambiguous evidence of regulation, especially when accounting for effects of observation error. Here, we reexamine the evidence for density dependence in time series of population sizes in nature, by conducting an aggregate analysis of the populations in the Global Population Dynamics Database (GPDD). First, following the conventional approach, we fit a density-dependent and a density-independent variant of the Gompertz state-space model to each time series. Then, we conduct an aggregate analysis of the entire database by considering two random-effects density-dependent models that leverage information across data sets. When individual time series are tested independently, we find very little evidence for density dependence. However, in the aggregate, we find very strong evidence for density dependence, even though, paradoxically, estimated strengths of density dependence for individual time series tend to be weaker than when each individual time series is analyzed independently. Furthermore, a hierarchical model that accounts for taxonomic variation in the strength of density dependence reveals that density dependence is consistently stronger in insects and fish than in birds and mammals. Our findings resolve apparent inconsistencies between observational and experimental studies of density dependence by revealing that the observational record does indeed contain strong support for the hypothesis that density dependence is widespread in nature.
Journal Article
Ensemble Kalman Methods for High-Dimensional Hierarchical Dynamic Space-Time Models
We propose a new class of filtering and smoothing methods for inference in high-dimensional, nonlinear, non-Gaussian, spatio-temporal state-space models. The main idea is to combine the ensemble Kalman filter and smoother, developed in the geophysics literature, with state-space algorithms from the statistics literature. Our algorithms address a variety of estimation scenarios, including online and off-line state and parameter estimation. We take a Bayesian perspective, for which the goal is to generate samples from the joint posterior distribution of states and parameters. The key benefit of our approach is the use of ensemble Kalman methods for dimension reduction, which allows inference for high-dimensional state vectors. We compare our methods to existing ones, including ensemble Kalman filters, particle filters, and particle MCMC. Using a real data example of cloud motion and data simulated under a number of nonlinear and non-Gaussian scenarios, we show that our approaches outperform these existing methods.
Supplementary materials
for this article are available online.
Journal Article
Reaching for the moon : a short history of the space race
At the dawn of the space age, technological breakthroughs in Earth orbit flight were both breathtaking feats of ingenuity and disturbances to a delicate global balance of power. In this short book, aerospace historian Roger D. Launius concisely and engagingly explores the driving force of this era: the race to the Moon. Beginning with the launch of Sputnik 1 in October 1957 and closing with the end of the Apollo program in 1972, Launius examines how early space exploration blurred the lines between military and civilian activities, and how key actions led to space firsts as well as crushing failures. Launius places American and Soviet programs on equal footing-following American aerospace engineers Wernher von Braun and Robert Gilruth, their Soviet counterparts Sergei Korolev and Valentin Glushko, and astronaut Buzz Aldrin and cosmonaut Alexei Leonov-to highlight key actions that led to various successes, failures, and ultimately the American Moon landing.
Book
Understanding the Ensemble Kalman Filter
The ensemble Kalman filter (EnKF) is a computational technique for approximate inference in state-space models. In typical applications, the state vectors are large spatial fields that are observed sequentially over time. The EnKF approximates the Kalman filter by representing the distribution of the state with an ensemble of draws from that distribution. The ensemble members are updated based on newly available data by shifting instead of reweighting, which allows the EnKF to avoid the degeneracy problems of reweighting-based algorithms. Taken together, the ensemble representation and shifting-based updates make the EnKF computationally feasible even for extremely high-dimensional state spaces. The EnKF is successfully used in data-assimilation applications with tens of millions of dimensions. While it implicitly assumes a linear Gaussian state-space model, it has also turned out to be remarkably robust to deviations from these assumptions in many applications. Despite its successes, the EnKF is largely unknown in the statistics community. We aim to change that with the present article, and to entice more statisticians to work on this topic.
Journal Article
Computational analysis of an infinite magneto-thermoelastic solid periodically dispersed with varying heat flow based on non-local Moore–Gibson–Thompson approach
In this investigation, a computational analysis is conducted to study a magneto-thermoelastic problem for an isotropic perfectly conducting half-space medium. The medium is subjected to a periodic heat flow in the presence of a continuous longitude magnetic field. Based on Moore–Gibson–Thompson equation, a new generalized model has been investigated to address the considered problem. The introduced model can be formulated by combining the Green–Naghdi Type III and Lord–Shulman models. Eringen’s non-local theory has also been applied to demonstrate the effect of thermoelastic materials which depends on small scale. Some special cases as well as previous thermoelasticity models are deduced from the presented approach. In the domain of the Laplace transform, the system of equations is expressed and the problem is solved using state space method. The converted physical expressions are numerically reversed by Zakian’s computational algorithm. The analysis indicates the significant influence on field variables of non-local modulus and magnetic field with larger values. Moreover, with the established literature, the numerical results are satisfactorily examined.
Journal Article