Captain Frank Jones, a famed nineteenth-century Texas Ranger, said of his company-s top sergeant, Baz Outlaw (1854-1894), "A man of unusual courage and coolness and in a close place is worth two or three ordinary men." Another old-time Texas Ranger declared that Baz Outlaw "was one of the worst and most dangerous" because "he never knew what fear was." But not all thought so highly of him. In Whiskey River Ranger, Bob Alexander tells for the first time the full story of this troubled Texas Ranger and his losing battle with alcoholism. In his career Baz Outlaw wore a badge as a Texas Ranger and also as a Deputy U.S. Marshal. He could be a fearless and crackerjack lawman, as well as an unmanageable manic. Although Baz Outlaw's badge-wearing career was sometimes heroically creditable, at other times his self-induced nightmarish imbroglios teased and tested Texas Ranger management's resoluteness. Baz Outlaw's true-life story is jam-packed with fellows owning well-known names, including Texas Rangers, city marshals, sheriffs, and steely-eyed mean-spirited miscreants. Baz Outlaw's tale is complete with horseback chases, explosive train robberies, vigilante justice (or injustice), nighttime ambushes and bushwhacking, and episodes of scorching six-shooter finality. Baz met his end in a brothel brawl at the hands of John Selman, the same gunfighter who killed John Wesley Hardin.
A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students—whether from the life sciences, physics, computational sciences, engineering, or mathematics—how to reason quantitatively in the face of uncertainty. Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communities Encourages good coding practices, clear and understandable modeling, and accessible presentation of results Helps students to develop a diverse repertoire of simulation approaches, enabling them to model at the appropriate scale Builds practical expertise in a range of methods, including sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulations Bridges the gap between the classroom and research discovery, helping students to think independently, troubleshoot and resolve problems, and embark on research of their own Stand-alone computational lab guides for Quantitative Biosciences also available in R and MATLAB
Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research. Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population. Best of all, Python for the Life Sciences shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you. What You'll Learn Write Python scripts to automate your lab calculations Search for important motifs in genome sequences Use object-oriented programming with Python Study mining interaction network data for patterns Review dynamic modeling of biochemical switches Who This Book Is For Life scientists with little or no programming experience, including undergraduate and graduate students, postdoctoral researchers in academia and industry, medical professionals, and teachers/lecturers. “A comprehensive introduction to using Python for computational biology... A lovely book with humor and perspective” -- John Novembre, Associate Professor of Human Genetics, University of Chicago and MacArthur Fellow “Fun, entertaining, witty and darn useful. A magical portal to the big data revolution” -- Sandro Santagata, Assistant Professor in Pathology, Harvard Medical School “Alex and Gordon’s enthusiasm for Python is contagious” -- Glenys Thomson Professor of Integrative Biology, University of California, Berkeley
Life histories can be defined as the means by which individuals (or more precisely genotypes) vary their age- or stage-specific expenditures of reproductive effort in response to genetic, phenotypic, and environmental correlates of survival and fecundity. Life histories reflect the expression of traits most closely related to individual fitness, such as age and size at maturity, number and size of offspring, and the timing of the expression of those traits throughout an individual's life. In addition to addressing questions of fundamental importance to ecology and evolution, life-history research plays an integral role in species conservation and management. This accessible primer encompasses the basic concepts, theories, and applied elements of life history evolution, including patterns of trait variability, underlying mechanisms of plastic/evolutionary change, and the practical utility of life-history traits as metrics of species/population recovery, sustainable exploitation, and risk of extinction. Empirical examples are drawn from the entire spectrum of life. A Primer of Life Histories is designed for readers from a broad range of academic backgrounds and experience including graduate students and researchers of ecology and evolutionary biology. It will also be useful to a more applied audience of academic/government researchers in fields such as wildlife biology, conservation biology, fisheries science, and the environmental sciences.
Why did precarious and collapsed democracies in Europe develop into highly stable democracies? Gerard Alexander offers a rational choice theory of democratic consolidation in a survey of the breakdowns of and transitions to democratic institutions. Through an analysis of developments in Spain, Britain, France, Germany, and Italy, Alexander explores how key political sectors established the long-term commitment to democracy that distinguishes consolidated democracies. Alexander makes a highly accessible rationalist argument about the conditions under which such commitments emerge, arguing that powerful sectors abandon options for overthrowing democratic rules only when they predict low risks in democracy. The author's argument parallels established claims about the predictability essential to the development of modern capitalism. The Sources of Democratic Consolidation outlines Alexander's claim that a political precondition, rather than an economic or social precondition, exists for consolidated democracies. Drawing on interviews and archival research, the author links his argument to evidence from the five largest countries in Western Europe from the 1870s to the 1980s and also discusses the implications for the prospects for democratic consolidation in other regions. Political pacts, power-sharing, and institutional designs, he says, may help stabilize uncertain democracies, but they cannot create consolidation.
The talented black cricketers who toured England in 1868 have become one of Australia's enduring sporting legends. Aboriginal sporting heroes are found in many sports today, from football to tennis, boxing and athletics, but it was very different in the nineteenth century when the pastoral frontier was still bitterly disputed by whites and blacks. Aboriginal workers on the Wimmera sheep stations began to develop and organise their cricketing skills during the 1860s and were recruited into a team by station owner and former Test cricketer Tom Wills. On Boxing Day 1866 they played before 8000 people at the MCG, followed by a disastrous Sydney tour which lead to the deaths of some players. Former test player Ashley Mallet has dramatically reconstructed this important pioneering tour of England and has also included the careers of later black players, including the famous fast bowler Eddie Gilbert who died tragically without fulfilling his potential.
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