Humanism and Religion in Early Modern Spain brings together twenty-five essays by renowned historian Terence O’Reilly. The essays examine the interplay of religion and humanism in a series of writings composed in sixteenth-century Spain. It begins by presenting essential background: the coming together during the reign of the Emperor Charles V of Erasmian humanism and various movements of religious reform, some of them heterodox. It then moves on to the reign of Philip II, focusing on the mystical poetry and prose of St John of the Cross. It explores the influence on his writings of his humanist learning – classical, biblical and patristic. The third part of the book concerns a verse-epistle by John’s contemporary, Francisco de Aldana. One chapter presents the text with a parallel version in English, whilst two others trace its debt to Florentine Neoplatonism, particularly the thought of Marsilio Ficino. The final part is devoted to the humanism of the poet and Scripture scholar Luis de León, and specifically to the confluence in his work of biblical and classical motifs. This book is essential reading for scholars and students of early modern Spanish history, as well those interested in literary studies and the history of religion. (CS 1102).

Translated by P. A. Motteux With an Introduction and Notes by Stephen Boyd, University College, Cork Cervantes' tale of the deranged gentleman who turns knight-errant, tilts at windmills and battles with sheep in the service of the lady of his dreams, Dulcinea del Toboso, has fascinated generations of readers, and inspired other creative artists such as Flaubert, Picasso and Richard Strauss. The tall, thin knight and his short, fat squire, Sancho Panza, have found their way into films, cartoons and even computer games. Supposedly intended as a parody of the most popular escapist fiction of the day, the 'books of chivalry', this precursor of the modern novel broadened and deepened into a sophisticated, comic account of the contradictions of human nature. On his 'heroic' journey Don Quixote meets characters of every class and condition, from the prostitute Maritornes, who is commended for her Christian charity, to the Knight of the Green Coat, who seems to embody some of the constraints of virtue. Cervantes' greatest work can be enjoyed on many levels, all suffused with a subtle irony that reaches out to encompass the reader, and does not leave the author outside its circle. Peter Motteux's fine eighteenth-century translation, acknowledged as one of the best, brilliantly succeeds in communicating the spirit of the original Spanish.

Humanism and Religion in Early Modern Spain brings together twenty-five essays by renowned historian Terence O'Reilly. The essays examine the interplay of religion and humanism in a series of writings composed in sixteenth-century Spain. It begins by presenting essential background: the coming together during the reign of the Emperor Charles V of Erasmian humanism and various movements of religious reform, some of them heterodox. It then moves on to the reign of Philip II, focusing on the mystical poetry and prose of St John of the Cross. It explores the influence on his writings of his humanist learning - classical, biblical and patristic. The third part of the book concerns a verse-epistle by John's contemporary, Francisco de Aldana. One chapter presents the text with a parallel version in English, whilst two others trace its debt to Florentine Neoplatonism, particularly the thought of Marsilio Ficino. The final part is devoted to the humanism of the poet and Scripture scholar Luis de Leon, and specifically to the confluence in his work of biblical and classical motifs. This book is essential reading for scholars and students of early modern Spanish history, as well those interested in literary studies and the history of religion.

In autumn 1397, Viscount Ramon de Perellos left the papal palace in Avignon to travel to St Patrick's Purgatory, famous throughout Europe as a gateway to the next world. There, he spent twenty-four hours in an underground cavern, where he claimed to have travelled through the nine fields of Purgatory, accompanied by demons, before entering the Earthly Paradise and catching a glimpse of Heaven.

Updating the extremely successful Wildlife Toxicology and Population Modeling (CRC Press, 1994), Wildlife Toxicology: Emerging Contaminant and Biodiversity Issues brings together a distinguished group of international contributors, who provide a global assessment of a range of environmental stressors, including pesticides, environmental contaminants, and other emerging chemical threats, and their impact on wildlife populations.

Addresses Emerging Wildlife Threats in One Concise Volume

A decade ago, many of these threats existed but were either unrecognized or considered minor issues, and all have now snowballed into major challenges for the conservation of wildlife populations. This is the first book to address these dangers in a single volume and recommend proven mitigation techniques to protect and sustain Earth's wildlife populations.

Examines Species Range Shifts, Ocean Acidification, Coral Bleaching, & Impacts of Heightened UV Influx

This comprehensive reference identifies and documents examples of chemical stressor exposures and responses among ecosystem receptors worldwide. Chapters discuss emerging diseases and the expansion of pesticide/contaminant use, as well as agricultural trends and biofuels, and the widespread use of munitions and explosives from military and industrial-related activities. With the aid of several solid case studies, the book also addresses atmospheric contaminants and climate change, population modeling, and emerging transnational issues in ecotoxicology.

Wildlife Toxicology: Emerging Contaminant and Biodiversity Issues stimulates dialogue among the academic and research communities and environmental public policy decision makers. The book challenges these groups to think more globally about environmental contaminants and their potential impacts on biodiversity and environmental degradation.

Check out Ronald J. Kendall's Advances in Biological and Chemical Terrorism Countermeasures.

Professor Kendall has been quoted recently in several news outlets in connection with the Gulf Oil Spill. Check out these articles on the CRC Press Ning page.

This book showcases the research of established and younger colleagues from Great Britain and Ireland on artifice and invention in the Spanish Golden Age. It falls into four sections, in each of which works on particular authors are examined in detail: prose, poetry, drama, and colonial writing.

Heritage Tourism provides a balanced view of both theoretical issues and applied subjects that managers must deal with on a daily basis. These concepts are illustrated throughout the text via examples and boxed case studies. With the rapid growth of special interest travel during the past two decades, the demand for heritage tourism experiences has soared, and its economic and socio-cultural importance cannot be overstated. This book addresses this booming type of tourism and will prove to be a valuable resource for educators, students, and practitioners in the field of heritage tourism.

The corpus of literary works shaped by the Renaissance and the Baroque that appeared in Spain during the sixteenth and seventeenth centuries had a transforming effect on writing throughout Europe and left a rich legacy that scholars continue to explore. For four decades after the Spanish Civil War the study of this literature flourished in Great Britain and Ireland, where many of the leading scholars in the field were based. Though this particular Golden Age was followed by a decline for many years, there have recently been signs of a significant revival. The present book seeks to showcase the latest research of established and younger colleagues from Great Britain and Ireland on the Spanish Golden Age. It falls into four sections, in each of which works by particular authors are examined in detail: prose (Miguel de Cervantes, Francisco de Quevedo, Baltasar Gracian), poetry (The Count of Salinas, Luis de Gongora, Pedro Soto de Rojas), drama (Cervantes, Calderon, Lope de Vega), and colonial writing (Bernardo Balbuena, Hernando Dominguez Camargo, Alonso de Ercilla). There are essays also on more general themes (the motif of poetry as manna; rehearsals on the Golden Age stage; proposals put to viceroys on governing Spanish Naples). The essays, taken together, offer a representative sample of current scholarship in England, Scotland, and Ireland."

This edited volume of fourteen specially commissioned essays written from a variety of critical perspectives by leading Cervantine scholars seeks to provide an overview of Cervantes's Novelas ejemplares which will be of interest to a broad academic readership. This edited volume of fourteen specially commissioned essays written from a variety of critical perspectives by leading cervantine scholars seeks to provide an overview of Cervantes's Novelas ejemplares which will be of interest to a broad academic readership. An extensive general Introduction places the Novelas in the context of Cervantes's life and work; provides basic information about their content, composition, internal ordering, publication, and critical reception, gives detailed consideration to the contemporary literary-theoretical issues implicit in the title, and outlines and contributes to the key critical debates on their variety, unity, exemplarity,and supposed 'hidden mystery'. After a series of chapters on the individual stories, the volume concludes with two survey essays devoted, respectively, to the understanding of eutrapelia implicit in the Novelas, andto the dynamics of the character pairing that is one of their salient features. Detailed plot summaries of each of the stories, and a Guide to Further Reading are supplied as appendices. Stephen Boyd is a lecturer in the Department of Hispanic Studies of University College Cork.

Updating the extremely successful Wildlife Toxicology and Population Modeling (CRC Press, 1994), Wildlife Toxicology: Emerging Contaminant and Biodiversity Issues brings together a distinguished group of international contributors, who provide a global assessment of a range of environmental stressors, including pesticides, environmental contaminants, and other emerging chemical threats, and their impact on wildlife populations. Addresses Emerging Wildlife Threats in One Concise Volume A decade ago, many of these threats existed but were either unrecognized or considered minor issues, and all have now snowballed into major challenges for the conservation of wildlife populations. This is the first book to address these dangers in a single volume and recommend proven mitigation techniques to protect and sustain Earth's wildlife populations. Examines Species Range Shifts, Ocean Acidification, Coral Bleaching, & Impacts of Heightened UV Influx This comprehensive reference identifies and documents examples of chemical stressor exposures and responses among ecosystem receptors worldwide. Chapters discuss emerging diseases and the expansion of pesticide/contaminant use, as well as agricultural trends and biofuels, and the widespread use of munitions and explosives from military and industrial-related activities. With the aid of several solid case studies, the book also addresses atmospheric contaminants and climate change, population modeling, and emerging transnational issues in ecotoxicology. Wildlife Toxicology: Emerging Contaminant and Biodiversity Issues stimulates dialogue among the academic and research communities and environmental public policy decision makers. The book challenges these groups to think more globally about environmental contaminants and their potential impacts on biodiversity and environmental degradation.

Building upon the book Disappearing Destinations (Jones and Phillips 2010) and its conclusion that promoted the need to recognize problems, meet expectations and manage solutions Global Climate Change and Coastal Tourism explores current threats to, and consequences of, climate change on existing tourism coastal destinations. Part 1 of the book provides a theoretical platform and addresses topics such as sustainability, tourism impacts, governance trade and innovation and how the media addresses climate change and tourism. It also assesses management and policy options for the future sustainability of threatened tourism coastal destinations. Part 2 presents case studies from all regions of the world (Europe, The Americas, Asia, Africa and Australasia) which synthesise findings to make recommendations that can be used to promote strategies that ameliorate projected impacts of climate change on coastal tourism infrastructure and in turn promote the future sustainability of coastal tourism destinations. This is a timely and informative text with appeal to researchers, undergraduate and post graduate students of tourism management, tourism planning, sustainable tourism development and leisure management, coastal tourism/management, environmental management/planning, geography, coastal zone management or climate change studies.

This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance. The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving real-world problems, with lecture slides, additional computational exercises in Julia and MATLAB (R), and data sets accompanying the book online. Suitable for both one-semester and one-quarter courses, as well as self-study, this self-contained text provides beginning students with the foundation they need to progress to more advanced study.

This edited volume of fourteen specially commissioned essays written from a variety of critical perspectives by leading Cervantine scholars seeks to provide an overview of Cervantes's Novelas ejemplares which will be of interest to a broad academic readership. This edited volume of fourteen specially commissioned essays written from a variety of critical perspectives by leading cervantine scholars seeks to provide an overview of Cervantes's Novelas ejemplares which will be of interest to a broad academic readership. An extensive general Introduction places the Novelas in the context of Cervantes's life and work; provides basic information about their content, composition, internal ordering, publication, and critical reception, gives detailed consideration to the contemporary literary-theoretical issues implicit in the title, and outlines and contributes to the key critical debates on their variety, unity, exemplarity,and supposed "hidden mystery". After a series of chapters on the individual stories, the volume concludes with two survey essays devoted, respectively, to the understanding of eutrapelia implicit in the Novelas, andto the dynamics of the character pairing that is one of their salient features. Detailed plot summaries of each of the stories, and a Guide to Further Reading are supplied as appendices. Stephen Boyd is a lecturer in the Department of Hispanic Studies of University College Cork.

Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Embeddings provide concrete numerical representations of otherwise abstract items, for use in downstream tasks. For example, a biologist might look for subfamilies of related cells by clustering embedding vectors associated with individual cells, while a machine learning practitioner might use vector representations of words as features for a classification task. In this monograph the authors present a general framework for faithful embedding called minimum-distortion embedding (MDE) that generalizes the common cases in which similarities between items are described by weights or distances. The MDE framework is simple but general. It includes a wide variety of specific embedding methods, including spectral embedding, principal component analysis, multidimensional scaling, Euclidean distance problems, etc.The authors provide a detailed description of minimum-distortion embedding problem and describe the theory behind creating solutions to all aspects. They also give describe in detail algorithms for computing minimum-distortion embeddings. Finally, they provide examples on how to approximately solve many MDE problems involving real datasets, including images, co-authorship networks, United States county demographics, population genetics, and single-cell mRNA transcriptomes.An accompanying open-source software package, PyMDE, makes it easy for practitioners to experiment with different embeddings via different choices of distortion functions and constraint sets.The theory and techniques described and illustrated in this book will be of interest to researchers and practitioners working on modern-day systems that look to adopt cutting-edge artificial intelligence.

Multi-Period Trading via Convex Optimization considers a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. It describes a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades off expected return, risk, transaction cost and holding cost such as the borrowing cost for shorting assets. It then describes a multiperiod version of the trading method, where optimization is used to plan a sequence of trades, with only the first one executed, using estimates of future quantities that are unknown when the trades are chosen. The single period method traces back to Markowitz; the multiperiod methods trace back to model predictive control. This monograph addresses the single-period and multi-period methods in one simple framework, giving a clear description of the development and the approximations made. The methods described can be thought of as good ways to exploit predictions, no matter how they are made. We have also developed a companion open-source software library that implements many of the ideas and methods described in the paper. Multi-Period Trading via Convex Optimization collects in one place the basic definitions, a careful description of the model, and discussion of how convex optimization can be used in multi-period trading, all in a common notation and framework. It provides the reader with a unified, self-contained treatment, focusing on the practical issues that arise in multi-period trading. It will benefit anyone interested in the study of these methods and is also an ideal reference for a quantitative trader, or someone who works with or for, or employs, one.

Principal components analysis (PCA) is a well-known technique for approximating a tabular data set by a low rank matrix. Here, the authors extend the idea of PCA to handle arbitrary data sets consisting of numerical, Boolean, categorical, ordinal, and other data types. This framework encompasses many well-known techniques in data analysis, such as non-negative matrix factorization, matrix completion, sparse and robust PCA, k-means, k-SVD, and maximum margin matrix factorization. The method handles heterogeneous data sets, and leads to coherent schemes for compressing, denoising, and imputing missing entries across all data types simultaneously. It also admits a number of interesting interpretations of the low rank factors, which allow clustering of examples or of features. The authors propose several parallel algorithms for fitting generalized low rank models, and describe implementations and numerical results.

Proximal Algorithms discusses proximal operators and proximal algorithms, and illustrates their applicability to standard and distributed convex optimization in general and many applications of recent interest in particular. Much like Newton's method is a standard tool for solving unconstrained smooth optimization problems of modest size, proximal algorithms can be viewed as an analogous tool for nonsmooth, constrained, large-scale, or distributed versions of these problems. They are very generally applicable, but are especially well-suited to problems of substantial recent interest involving large or high-dimensional datasets. Proximal methods sit at a higher level of abstraction than classical algorithms like Newton's method: the base operation is evaluating the proximal operator of a function, which itself involves solving a small convex optimization problem. These subproblems, which generalize the problem of projecting a point onto a convex set, often admit closed-form solutions or can be solved very quickly with standard or simple specialized methods. Proximal Algorithms discusses different interpretations of proximal operators and algorithms, looks at their connections to many other topics in optimization and applied mathematics, surveys some popular algorithms, and provides a large number of examples of proximal operators that commonly arise in practice.

Presents a fully decentralized method for dynamic network energy management based on message passing between devices. It considers a network of devices, such as generators, fixed loads, deferrable loads, and storage devices, each with its own dynamic constraints and objective, connected by AC and DC lines. The problem is to minimize the total network objective subject to the device and line constraints, over a given time horizon. This is a large optimization problem, with variables for consumption or generation for each device, power flow for each line, and voltage phase angles at AC buses, in each time period. This text develops a decentralized method for solving this problem called proximal message passing. The method is iterative: at each step, each device exchanges simple messages with its neighbors in the network and then solves its own optimization problem, minimizing its own objective function, augmented by a term determined by the messages it has received. It is shown that this message passing method converges to a solution when the device objective and constraints are convex. The method is completely decentralized, and needs no global coordination other than synchronizing iterations; the problems to be solved by each device can typically be solved extremely efficiently and in parallel. The method is fast enough that even a serial implementation can solve substantial problems in reasonable time frames. Results for several numerical experiments are reported, demonstrating the method's speed and scaling, including the solution of a problem instance with over ten million variables in under fifty minutes for a serial implementation; with decentralized computing, the solve time would be less than one second.

Examines dynamic trading of a portfolio of assets in discrete periods over a finite time horizon, with arbitrary time-varying distribution of asset returns. The goal is to maximize the total expected revenue from the portfolio, while respecting constraints on the portfolio like a required terminal portfolio and leverage and risk limits. The revenue takes into account the gross cash generated in trades, transaction costs, and costs associated with the positions, such as fees for holding short positions. The model that is presented takes the form of a stochastic control problem with linear dynamics and convex cost function and constraints. While this problem can be tractably solved in several special cases - for example, when all costs are convex quadratic, or when there are no transaction costs - the focus is on the more general case, with nonquadratic cost terms and transaction costs. Performance Bounds and Suboptimal Policies for Multi-Period Investment shows how to use linear matrix inequality techniques and semidefinite programming to produce a quadratic bound on the value function, which in turn gives a bound on the optimal performance. This performance bound can be used to judge the performance obtained by any suboptimal policy. As a by-product of the performance bound computation, an approximate dynamic programming policy is obtained that requires the solution of a convex optimization problem, often a quadratic program, to determine the trades to carry out in each step.

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a very large number of features or training examples. As a result, both the decentralized collection or storage of these datasets as well as accompanying distributed solution methods are either necessary or at least highly desirable. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers argues that the alternating direction method of multipliers is well suited to distributed convex optimization, and in particular to large-scale problems arising in statistics, machine learning, and related areas. The method was developed in the 1970s, with roots in the 1950s, and is equivalent or closely related to many other algorithms, such as dual decomposition, the method of multipliers, Douglas-Rachford splitting, Spingarn's method of partial inverses, Dykstra's alternating projections, Bregman iterative algorithms for 1 problems, proximal methods, and others. After briefly surveying the theory and history of the algorithm, it discusses applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others. It also discusses general distributed optimization, extensions to the nonconvex setting, and efficient implementation, including some details on distributed MPI and Hadoop MapReduce implementations