The sudden dissolution of the Soviet Union altered the routines, norms, celebrations, and shared understandings that had shaped the lives of Russians for generations. It also meant an end to the state-sponsored, nonmonetary support that most residents had lived with all their lives. How did Russians make sense of these historic transformations? Serguei Alex. Oushakine offers a compelling look at postsocialist life in Russia. In Barnaul, a major industrial city in southwestern Siberia that has lost 25 percent of its population since 1991, many Russians are finding that what binds them together is loss and despair. The Patriotism of Despair examines the aftermath of the collapse of the Soviet Union, graphically described in spray paint by a graffiti artist in Barnaul: "We have no Motherland." Once socialism disappeared as a way of understanding the world, what replaced it in people's minds? Once socialism stopped orienting politics and economics, how did capitalism insinuate itself into routine practices? Oushakine offers a compelling look at postsocialist life in noncosmopolitan Russia. He introduces readers to the "neocoms": people who mourn the loss of the Soviet economy and the remonetization of transactions that had not involved the exchange of cash during the Soviet era. Moving from economics into military conflict and personal loss, Oushakine also describes the ways in which veterans of the Chechen war and mothers of soldiers who died there have connected their immediate experiences with the country's historical disruptions. The country, the nation, and traumatized individuals, Oushakine finds, are united by their vocabulary of shared pain.
Journey behind enemy lines in Second World War Europe with the The Spy Masters Thrillers. Includes all four books in the series; The Best of Our Spies, The Swiss Spy, Vienna Spies and The Berlin Spies. The Best of Our Spies: In the Pas de Calais, Nathalie Mercier, a young British Special Operations Executive secret agent working with the French Resistance, disappears. In London, her husband Owen Quinn, an officer with Royal Navy Intelligence, discovers the truth about her role in the Allies’ sophisticated deception at the heart of D-Day. Appalled but determined, Quinn sets off on a perilous hunt through France in search of his wife. Aided by the Resistance in his search, he makes good progress. But, caught up by the bitterness of the war and its insatiable appetite for revenge, he risks total destruction... The Swiss Spy: All spies have secrets, but Henry Hunter has more than most. After he is stopped by British Intelligence at Croydon airport on the eve of the Second World War, he discovers one more devastating than any before. From Switzerland he embarks on a series of increasingly perilous missions into Nazi Germany. In March, 1941, in Berlin, haunted by a dark episode from his past, he makes a fateful decision, resulting in a dramatic journey to the Swiss frontier and a shocking encounter... Vienna Spies: With the end of the Second World War in sight, the Allies begin to divide up the spoils and it proves to be a dangerous game. The British have become aware that, contrary to prior agreements, the Soviet Union is intent on controlling Austria once the war ends. Major Edgar is tasked with the job of establishing an espionage unit in Vienna to monitor the situation. He sends in two agents – Rolf Eder and Katharina Hoch – to track down Austria's most respected politician and bring him over to the British cause. But the feared Soviet spy Viktor Krasotkin is already in the war-torn city, embarking on exactly the same mission... The Berlin Spies: Berlin, 1945. SS recruits gather east of the city for an audacious yet ill-fated mission to bring about a Fourth Reich. Three decades later, a young British diplomat in East Berlin is compromised after falling into a honey-trap. He contacts Major Edgar, a veteran British spymaster, who is drawn into an unlikely alliance with his old adversary, Viktor Krasotkin. Soon they are plunged into a world of Nazi war criminals and double agents. With nobody to trust, they must rely on each other. But as Cold War tensions rise, the cracks begin to show. A masterclass in espionage fiction, these tense, tightly plotted novels are perfect for fans of John le Carré, Len Deighton and Jack Higgins. Praise for Alex Gerlis ‘A classic spy story, with twists and turns that keep you engrossed. Excellent.’ ⭐⭐⭐⭐⭐ Reader review ‘Brilliant... you cannot put it down. Spy thriller lovers must read this incredible story.’ ⭐⭐⭐⭐⭐ Reader review ‘The sense of time and place is second to none, and the characters are well drawn and very believable. A hugely satisfying and entertaining venture into the spy fiction genre.’ ⭐⭐⭐⭐⭐ Reader review ‘I couldn't put this down it grabbed my attention so well. Great attention to detail – like the Phillip Kerr or John Le Carre novels.’ ⭐⭐⭐⭐⭐ Reader review ‘Gerlis is always a superb read. He never fails to deliver a well researched spellbinder.’ ⭐⭐⭐⭐⭐ Reader review
The Second World War is coming to a close. But their fight is just beginning... Berlin, 1945: A group of Nazis frantically plot the next steps for their country. SS recruits gather east of the city for an audacious yet ill-fated mission to bring about a Fourth Reich. Three decades later, a young British diplomat in East Berlin is compromised after falling into a honey-trap. He contacts Major Edgar, a veteran British spymaster, who is drawn into an unlikely alliance with his old adversary, Viktor Krasotkin. Soon they are plunged into a world of Nazi war criminals and double agents. With nobody to trust, they must rely on each other. But as Cold War tensions rise, the cracks begin to show. The thrilling final novel in the Spies series, with an astonishing twist, perfect for fans of Jack Higgins, Frederick Forsyth and John le Carré.
This up-to-date and comprehensive account of theory and experiment on wave-interaction phenomena covers fluids both at rest and in their shear flows. It includes, on the one hand, water waves, internal waves, and their evolution, interaction, and associated wave-driven means flow and, on the other hand, phenomena on nonlinear hydrodynamic stability, especially those leading to the onset of turbulence. This study provide a particularly valuable bridge between these two similar, yet different, classes of phenomena. It will be of value to oceanographers, meteorologists, and those working in fluid mechanics, atmospheric and planetary physics, plasma physics, aeronautics, and geophysical and astrophysical fluid dynamics.
Molecular biology has now advanced to the point where it is no longer possible to give a complete review of the available data on the conformational features of proteins. New data keep streaming in, and there is obviously an urgent need for some sort of general treatment of the subject. A systematic treatment of the large amount of data obtained by a great variety of methods on a great variety of objects must be based on the use of models; these should be as simple as possible, should conform to well-established scien tific laws, and at the same time be sufficiently flexible. The validity of the models finally arrived at is then confirmed or otherwise by testing the conclusions arrived at with their aid by means of experiment. After a suitable model has been adopted, it can be used in analyzing the experimental data. Such an analysis may result in one of three possible situations: neither the experi mental results nor their interpretation contradict the proposed model; the experimental results do not contradict the proposed model but their interpretation by the authors does; finally, both the experimental results and their interpretation may be found to be incompatible with the fundamental principles underlying the proposed model. The first situation is clearly the most desirable, and presents no difficulties.
Challenges conventional jazz historiography by demonstrating the role of big bands in the development of jazz. This book describes how jazz musicians found big bands valuable. It explores the rehearsal band scene in New York and rise of orchestras. It combines historical research, ethnography, and participant observation with musical analysis.
Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop About This Book This is a primer on functional-programming-style techniques to help you efficiently process and analyze all of your data Get acquainted with the best and newest tools available such as Scala, Spark, Parquet and MLlib for machine learning Learn the best practices to incorporate new Big Data machine learning in your data-driven enterprise to gain future scalability and maintainability Who This Book Is For Mastering Scala Machine Learning is intended for enthusiasts who want to plunge into the new pool of emerging techniques for machine learning. Some familiarity with standard statistical techniques is required. What You Will Learn Sharpen your functional programming skills in Scala using REPL Apply standard and advanced machine learning techniques using Scala Get acquainted with Big Data technologies and grasp why we need a functional approach to Big Data Discover new data structures, algorithms, approaches, and habits that will allow you to work effectively with large amounts of data Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level and help you impart that knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala. Style and approach This hands-on guide dives straight into implementing Scala for machine learning without delving much into mathematical proofs or validations. There are ample code examples and tricks that will help you sail through using the standard techniques and libraries. This book provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.
Whilst Soviet communism and its relationship with modernity has been widely studied to date, the agrarian experiment in Eastern Europe has been relegated to the margins of historical analysis. In this comparative study, Alex Toshkov uncovers the history of agrarianism after the First World War and explores its place as an alternative modernity to liberal democracy and capitalism. Drawing on a wealth of archival material, this book explores the transnational connections between the paradigmatic cases of Bulgaria, Yugoslavia and Czechoslovakia, as well as the International Agrarian Bureau in Prague, teasing out contradictions, hidden records and silenced interpretations of agrarianism. In addition, it uses a microhistorical approach to present an innovative theoretical framework which adds to our understanding of nationalism, political corruption, and alterity and the subaltern. This fascinating study restores interwar agrarianism to its rightful place as one of the most original and significant political currents in 20th-century Europe.
This new book examines the role of the Tsarist General Staff in studying and administering Russia’s Asian borderlands. It considers the nature of the Imperial Russian state, the institutional characteristics of the General Staff, and Russia’s relationship with Asia. During the nineteenth century, Russia was an important player in the so-called ‘Great Game’ in central Asia. Between 1800 and 1917 officers of the Russian General Staff travelled extensively through Turkey, central Asia and the Far East, gathering intelligence that assisted in the formation of future war plans. It goes on to consider tactics of imperial expansion, and the role of military intelligence and war planning with respect to important regions including the Caucasus, central Asia and the Far East. In the light of detailed archival research, it investigates objectively questions such as the possibility of Russia seizing the Bosphorus Straits, and the probability of an expedition to India. Overall, this book provides a comprehensive account of the Russian General Staff, its role in Asia, and of Russian military planning with respect to a region that remains highly strategically significant today.
Homogenization is a fairly new, yet deep field of mathematics which is used as a powerful tool for analysis of applied problems which involve multiple scales. Generally, homogenization is utilized as a modeling procedure to describe processes in complex structures. Applications of Homogenization Theory to the Study of Mineralized Tissue functions as an introduction to the theory of homogenization. At the same time, the book explains how to apply the theory to various application problems in biology, physics and engineering. The authors are experts in the field and collaborated to create this book which is a useful research monograph for applied mathematicians, engineers and geophysicists. As for students and instructors, this book is a well-rounded and comprehensive text on the topic of homogenization for graduate level courses or special mathematics classes. Features: Covers applications in both geophysics and biology. Includes recent results not found in classical books on the topic Focuses on evolutionary kinds of problems; there is little overlap with books dealing with variational methods and T-convergence Includes new results where the G-limits have different structures from the initial operators
First published in 1960, The Economy of Israel presents a critical account of the first ten years of Israeli economy. The book starts with a short description of the physical nature of the country and an examination of the Zionist ideas which played a decisive role in the formation of Israel. Part I of the book surveys the economy of Israel and traces the significant features of its development between 1948 and 1958. Part II is not a photograph of Israel’s exchange regulations at one particular date, but an eclectic account of the variable features of a flexible system that had but one constant factor, namely, the absence at any time of an effective unitary exchange rate. Part III of the book contains some general observations that are largely speculative. The book concludes with an examination of the prospects of Israel’s economy with special reference to the charitable aid which has provided it with its life blood during the first decade. This is an important historical account for scholars and researchers of economics, Middle East economics, and history of Israel.
Is Innovation just an overused buzzword? A waste of time? A mere marketing ploy? Author Alex Goryachev has a simple, resounding response to such questions: No! The Fourth Industrial Revolution is driving change at an unprecedented pace, level, and intensity that is impacting businesses across industries, not to mention our everyday lives. We are rapidly blurring the physical and the digital, transforming the way we live and, in some sense, what it even means to be human. Whether we run a startup or multinational, a nonprofit or academic institution, a city or a whole country, we need to embrace this change to not just survive but thrive under these new realities. In Fearless Innovation, Cisco’s Managing Director of Innovation Strategy and Programs explores how, no matter their function, leaders and managers can cut through the noise to understand change and deliver real results. Goryachev’s actionable, consistent, and timeless innovation principles offer a blueprint to driving growth, enacting change, increasing the bottom line, and creating clear measurable value. Featuring diverse case studies of some of today’s most innovative organizations, historical observations, first-hand experience, and a look at where innovation is thriving, and why, this down-to-earth guide provides advice and clear steps on how to: Get teams to embrace innovation beyond empty slogans Focus on execution of innovation through leadership and strategy Measure the real effects of innovation to showcase ROI and attract investment Break down org silos by empowering effective, diverse, and inclusive teams Drive co-innovation through win-win ecosystem-wide partnerships Organize innovation teams and orchestrate outcomes by leveraging organizational DNA Communicate the value of innovation to differentiate ourselves from competition Written for any organization that wants to stay relevant in the 21st Century, and even beyond, Fearless Innovation offers a step-by-step guide for getting past the confusion, overcoming fear, and getting down to business to create an environment of true innovation.
Are you looking for a journey that will take you through this amazing obok, along with funny comments and a word puzzle? Then this book is for you. Whether you are looking at this book for curiosity, choices, options, or just for fun; this book fits any criteria. Writing this book did not happen quickly. It is thorough look at accuracy and foundation before the book was even started. This book was created to inform, entertain and maybe even test your knowledge. By the time you finish reading this book you will want to share it with others.
The most important ingredient in the art of healing is the art of selling. I say that with all the respect in the world for every other part of this vast system of care that has grown into a sprawling and complex three-trillion-dollar metropolis. For the last sixty or so years, the providers of care have depended on third-party entities to handle the part of selling for them. From insurance companies who sold millions of people on the importance of paying monthly premiums for health-care insurance to the government that did the same thing under the more intimidating, compulsory taxation. Today, we have come to a fork in the road where (as the system implodes) those who control the flow of monetary resources are filling their own bank accounts, leaving the people who are busy providing care on that field of battle with all supply lines cut off. Many healers are, therefore, forced to shed all the entities that have forced themselves between the doctor and her patient. Exploring their original entrepreneurial roots, allowing the patient to bypass all middlemen and pay the doctor for care directly. The trouble comes in when the healing professional steps out of a world where all the marketing was handled for them and the only thing they needed to know was how to submit a bill to a third-party payer for reimbursement. So when embarking on this new journey of building a concierge, pay-for-service practice, many are derailed by the Flat Earth Fallacy that is a perception of things as they seem but are, in reality, very different. This book then is to share some field-tested experiences that will, in all probability, save the health-care entrepreneur some pain and expense, while providing a perspective on the driving elements of success in the art of selling the art of healing.
Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest features About This Book Build functional, type-safe routines to interact with relational and NoSQL databases with the help of the tutorials and examples provided Leverage your expertise in Scala programming to create and customize your own scalable machine learning algorithms Experiment with different techniques; evaluate their benefits and limitations using real-world financial applications Get to know the best practices to incorporate new Big Data machine learning in your data-driven enterprise and gain future scalability and maintainability Who This Book Is For This Learning Path is for engineers and scientists who are familiar with Scala and want to learn how to create, validate, and apply machine learning algorithms. It will also benefit software developers with a background in Scala programming who want to apply machine learning. What You Will Learn Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters Apply key learning strategies to perform technical analysis of financial markets Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail This Learning Path aims to put the entire world of machine learning with Scala in front of you. Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions. The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial. The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Scala for Data Science, Pascal Bugnion Scala for Machine Learning, Patrick Nicolas Mastering Scala Machine Learning, Alex Kozlov Style and approach A tutorial with complete examples, this course will give you the tools to start building useful data engineering and data science solutions straightaway. This course provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.
Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop About This Book This is a primer on functional-programming-style techniques to help you efficiently process and analyze all of your data Get acquainted with the best and newest tools available such as Scala, Spark, Parquet and MLlib for machine learning Learn the best practices to incorporate new Big Data machine learning in your data-driven enterprise to gain future scalability and maintainability Who This Book Is For Mastering Scala Machine Learning is intended for enthusiasts who want to plunge into the new pool of emerging techniques for machine learning. Some familiarity with standard statistical techniques is required. What You Will Learn Sharpen your functional programming skills in Scala using REPL Apply standard and advanced machine learning techniques using Scala Get acquainted with Big Data technologies and grasp why we need a functional approach to Big Data Discover new data structures, algorithms, approaches, and habits that will allow you to work effectively with large amounts of data Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level and help you impart that knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala. Style and approach This hands-on guide dives straight into implementing Scala for machine learning without delving much into mathematical proofs or validations. There are ample code examples and tricks that will help you sail through using the standard techniques and libraries. This book provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.
Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest features About This Book Build functional, type-safe routines to interact with relational and NoSQL databases with the help of the tutorials and examples provided Leverage your expertise in Scala programming to create and customize your own scalable machine learning algorithms Experiment with different techniques; evaluate their benefits and limitations using real-world financial applications Get to know the best practices to incorporate new Big Data machine learning in your data-driven enterprise and gain future scalability and maintainability Who This Book Is For This Learning Path is for engineers and scientists who are familiar with Scala and want to learn how to create, validate, and apply machine learning algorithms. It will also benefit software developers with a background in Scala programming who want to apply machine learning. What You Will Learn Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters Apply key learning strategies to perform technical analysis of financial markets Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail This Learning Path aims to put the entire world of machine learning with Scala in front of you. Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions. The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial. The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Scala for Data Science, Pascal Bugnion Scala for Machine Learning, Patrick Nicolas Mastering Scala Machine Learning, Alex Kozlov Style and approach A tutorial with complete examples, this course will give you the tools to start building useful data engineering and data science solutions straightaway. This course provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.
Here is a comprehensive, well-illustrated resource for anyone wishing to recreate or study the beautifully decorated Plains-style knife sheaths of the 19th and 20th centuries. Based on over 25 years of research and craftsmanship, the author describes the many styles and variation of Plains knife sheaths. Includes complete step-by-step instructions, full of illustrations, and numerous color photographs of knife sheaths produced by the author as well as those from both museum and private collections.
The sudden dissolution of the Soviet Union altered the routines, norms, celebrations, and shared understandings that had shaped the lives of Russians for generations. It also meant an end to the state-sponsored, nonmonetary support that most residents had lived with all their lives. How did Russians make sense of these historic transformations? Serguei Alex. Oushakine offers a compelling look at postsocialist life in Russia. In Barnaul, a major industrial city in southwestern Siberia that has lost 25 percent of its population since 1991, many Russians are finding that what binds them together is loss and despair. The Patriotism of Despair examines the aftermath of the collapse of the Soviet Union, graphically described in spray paint by a graffiti artist in Barnaul: "We have no Motherland." Once socialism disappeared as a way of understanding the world, what replaced it in people's minds? Once socialism stopped orienting politics and economics, how did capitalism insinuate itself into routine practices? Oushakine offers a compelling look at postsocialist life in noncosmopolitan Russia. He introduces readers to the "neocoms": people who mourn the loss of the Soviet economy and the remonetization of transactions that had not involved the exchange of cash during the Soviet era. Moving from economics into military conflict and personal loss, Oushakine also describes the ways in which veterans of the Chechen war and mothers of soldiers who died there have connected their immediate experiences with the country's historical disruptions. The country, the nation, and traumatized individuals, Oushakine finds, are united by their vocabulary of shared pain.
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