Quixotic Fictions of the USA 1792-1815 explores the conflicted and conflicting interpretations of Don Quixote available to and deployed by disenchanted writers of America's new republic. It argues that the legacy of Don Quixote provided an ambiguous cultural icon and ironic narrative stance that enabled authors to critique with impunity the ideological fictions shoring up their fractured republic. Close readings of works such as Modern Chivalry, Female Quixotism, and The Algerine Captive reveal that the fiction from this period repeatedly engaged with Cervantes's narrative in order to test competing interpretations of republicanism, to interrogate the new republic's multivalent crises of authority, and to question both the possibility and the desirability of an isolationist USA and an autonomous 'American' literature. Sarah Wood's study is the first book-length publication to examine the role of Don Quixote in early American literature. Exploring the extent to which the literary culture of North America was shaped by a diverse range of influences, it addresses an issue of growing concern to scholars of American history and literature. Quixotic Fictions reaffirms the global reach of Cervantes's influence and explores the complex, contradictory ways in which Don Quixote helped shape American fiction at a formative moment in its development.
Terrestrial Mammal Conservation provides a thorough summary of the available scientific evidence of what is known, or not known, about the effectiveness of all of the conservation actions for wild terrestrial mammals across the world (excluding bats and primates, which are covered in separate synopses). Actions are organized into categories based on the International Union for Conservation of Nature classifications of direct threats and conservation actions. Over the course of fifteen chapters, the authors consider interventions as wide ranging as creating uncultivated margins around fields, prescribed burning, setting hunting quotas and removing non-native mammals. This book is written in an accessible style and is designed to be an invaluable resource for anyone concerned with the practical conservation of terrestrial mammals. The authors consulted an international group of terrestrial mammal experts and conservationists to produce this synopsis. Funding was provided by the MAVA Foundation, Arcadia and National Geographic Big Cats Initiative. Terrestrial Mammal Conservation is the seventeenth publication in the Conservation Evidence Series, linked to the online resource www.ConservationEvidence.com. Conservation Evidence Synopses are designed to promote a more evidence-based approach to biodiversity conservation. Others in the series include Bat Conservation, Primate Conservation, Bird Conservation and Forest Conservation and more are in preparation. Expert assessment of the evidence summarised within synopses is provided online and within the annual publication What Works in Conservation.
This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data. The methods are based on fuzzy rough set theory, a mathematical framework used to model uncertainty in data. The book makes two main contributions: helping readers gain a deeper understanding of the underlying mathematical theory; and developing new, intuitive and well-performing classification approaches. The authors bridge the gap between the theoretical proposals of the mathematical model and important challenges in machine learning. The intended readership of this book includes anyone interested in learning more about fuzzy rough set theory and how to use it in practical machine learning contexts. Although the core audience chiefly consists of mathematicians, computer scientists and engineers, the content will also be interesting and accessible to students and professionals from a range of other fields.
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