Humankind has expanded out into interstellar space using star gates-technological remnants left behind by an ancient, long-vanished race. But the technology comes with a price. Among the stars, humanity encountered the Fallers, a strange alien race bent on nothing short of genocide. It's all-out war, and humanity is losing. In this fragile situation, a new planet is discovered, inhabited by a pre-industrial race who experience "shared reality"-they're literally compelled to share the same worldview. A team of human scientists is dispatched-but what they don't know is that their mission of first contact is actually a covert military operation. For one of the planet's moons is really a huge mysterious artifact of the same origin as the star gates . . . and it just may be the key to winning the war. At the Publisher's request, this title is being sold without Digital Rights Management Software (DRM) applied.

While expanding out into interstellar space using star gates left by an ancient, long-vanished race, humanity encounters the Fallers, an alien race bent on genocide. In this fragile situation, a new planet is discovered. A team of human scientists is sent to investigate the pre-industrial race living there. But what the scientists don't know is that their mission of first contact is actually a covert military operation.

Salvation or Annihilation? A strange artifact has been discovered on a distant planet, an artifact that may be the key to humanity's salvation. For we at war with the Fallers, an alien race bent on nothing short of genocide, and this is a war we are losing. The artifact is not only a powerful weapon, but possibly the rosetta stone to a lost superscience . . . a superscience that the Fallers may have already decoded. Or it may be a doomsday machine that could destroy the very fabric of space. At the Publisher's request, this title is being sold without Digital Rights Management Software (DRM) applied.

A group of scientists is sent to a distant planet to study an artifact that may hold the key to victory against the alien Fallers.

Nancy Kress cemented her reputation in SF with the publication of her multiple-award–winning novella, “Beggars in Spain,” which became the basis for her extremely successful Beggars Trilogy (comprising Beggars in Spain, Beggars and Choosers, and Beggars Ride). And now she brings us Probability Space, the conclusion of the trilogy that began with Probability Moon and then Probability Sun, which is centered on the same world as Kress’s Nebula Award-winning novelette, “Flowers of Aulit Prison.” The Probability Trilogy has already been widely recognized as the next great work by this important SF writer. In Probability Space, humanity’s war with the alien Fallers continues, and it is a war we are losing. Our implacable foes ignore all attempts at communication, and they take no prisoners. Our only hope lies with an unlikely coalition: Major Lyle Kaufman, retired warrior; Marbet Grant, the Sensitive who’s involved with Kaufman; Amanda, a very confused fourteen-year-old girl; and Magdalena, one of the biggest power brokers in all of human space. As the action moves from Earth to Mars to the farthest reaches of known space, with civil unrest back home and alien war in deep space, four humans--armed with little more than an unproven theory--try to enter the Fallers’ home star system. It’s a desperate gamble, and the fate of the entire universe may hang in the balance.

Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.

The only work to date to collect data gathered during the American and Soviet missions in an accessible and complete reference of current scientific and technical information about the Moon.