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Stamp Stomp

Miles Kelly: The Fastest Dinosaur

The Fastest Dinosaur

The Biggest Dinosaur

The Earthsalt Duology

Saltswept

Coercion and the Making of the Modern World

Empires of Labor

The Handbook of Infrastructure Communication

Excel as an HR Business Partner and support the business to meet its strategic objectives whilst meeting the needs of employees.

Aligning People Strategy with Business Goals

HR Business Partner Excellence

Why Liberals Must Win the Culture War

The New Dark Age

Series On Analysis, Applications And Computation

The book is devoted to rigorous mathematical results on discrete nonlinear Schrödinger equations (DNLS), including the initial value problem of the time-dependent DNLS and the standing wave of the stationary DNLS.The stationary DNLS equations emerge as equations for the profile of the standing wave in evolutionary DNLS. The book mainly presents well-localized, finite-energy solutions that represent solitary standing waves (breathers in the terminology of nonlinear science), while some other types of solutions are considered as well. The approach accepted in this book is variational, based on various critical point theorems of the mountain pass and linking type, as well as constrained minimization.The book covers the existence of solutions and their properties under various physically reasonable assumptions on linear and nonlinear potentials. It also contains a number of open problems which might be thesis topics for fresh PhD students. The results presented are scattered over a large number of research articles and have never been presented in a monograph form. In addition, there is necessary material from the spectral theory of discrete Schrödinger operators, time-dependent DNLS, and a brief presentation of critical point theorems used in the book.

Discrete Nonlinear Schrodinger Equation: Beyond Complete Integrability

With the rapid recent advances in the field of railway systems and infrastructure construction, and the evolution of AI tools that have enormous potential for application to railway design, maintenance and operations, industry professionals and researchers need an up-to-date resource on these developments. Artificial Intelligence Methods in Railway Infrastructure Systems: Application of Data Centric Engineering addresses this need. The book encapsulates the latest breakthroughs and contributions in these pivotal areas, providing readers with comprehensive insights into the cutting-edge methodologies and approaches shaping the field of railway infrastructure management. For engineers and researchers, the book provides a focused explanation of AI methodologies such as machine learning, computer vision and predictive analytics and their implementation to railway infrastructure development, tools that are new to this field. It combines theory with practical examples of the application of data centric engineering in structural health monitoring of monitoring of railway systems, thus enabling early anomaly detection and empowering infrastructure managers to address potential issues before they escalate. Given the expansive scope of research driving technological advancements in railway infrastructure management, this book serves as a reference for readers seeking to explore novel AI-based methodologies and harness their potential in the field. Readers will benefit from insights into how AI innovations can streamline their operations and enhance network safety across multiple dimensions. By providing a comprehensive overview of the subject matter, this book guides anticipatory strategies and shape future trends in railway infrastructure management.

The Fastest Dinosaur

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