This monograph contains papers that were delivered at the special session on Geometric Potential Analysis, that was part of the Mathematical Congress of the Americas 2021, virtually held in Buenos Aires. The papers, that were contributed by renowned specialists worldwide, cover important aspects of current research in geometrical potential analysis and its applications to partial differential equations and mathematical physics.

This book describes very recent results involving an extensive use of analytical tools in the study of geometrical and topological properties of complete Riemannian manifolds. It analyzes in detail an extension of the Bochner technique to the non compact setting, yielding conditions which ensure that solutions of geometrically significant differential equations either are trivial (vanishing results) or give rise to finite dimensional vector spaces (finiteness results). The book develops a range of methods, from spectral theory and qualitative properties of solutions of PDEs, to comparison theorems in Riemannian geometry and potential theory.

This monograph contains papers that were delivered at the special session on Geometric Potential Analysis, that was part of the Mathematical Congress of the Americas 2021, virtually held in Buenos Aires. The papers, that were contributed by renowned specialists worldwide, cover important aspects of current research in geometrical potential analysis and its applications to partial differential equations and mathematical physics.

Autonomous cars, drones, and electronic surveillance systems are examples of technologies that raise serious ethical issues. In this analytic investigation, Martin Peterson articulates and defends five moral principles for addressing ethical issues related to new and existing technologies: the cost-benefit principle, the precautionary principle, the sustainability principle, the autonomy principle, and the fairness principle. It is primarily the method developed by Peterson for articulating and analyzing the five principles that is novel. He argues that geometric concepts such as points, lines, and planes can be put to work for clarifying the structure and scope of these and other moral principles. This geometric account is based on the Aristotelian dictum that like cases should be treated alike, meaning that the degree of similarity between different cases can be represented as a distance in moral space. The more similar a pair of cases are from a moral point of view, the closer is their location in moral space. A case that lies closer in moral space to a paradigm case for some principle p than to any paradigm for any other principle should be analyzed by applying principle p. The book also presents empirical results from a series of experimental studies in which experts (philosophers) and laypeople (engineering students) have been asked to apply the geometric method to fifteen real-world cases. The empirical findings indicate that experts and laypeople do in fact apply geometrically construed moral principles in roughly, but not exactly, the manner advocates of the geometric method believe they ought to be applied.

Emphasizing integral formulas, the geometric theory of pseudoconvexity, estimates, partial differential equations, approximation theory, inner functions, invariant metrics, and mapping theory, this title is intended for the student with a background in real and complex variable theory, harmonic analysis, and differential equations.

Starting with the fundamentals of Qα spaces and their relationships to Besov spaces, this book presents all major results around Qα spaces obtained in the past 16 years. The applications of Qα spaces in the study of the incompressible Navier-Stokes system and its stationary form are also discussed. This self-contained book can be used as an essential reference for researchers and graduates in analysis and partial differential equations.

This book addresses the most efficient methods of pattern analysis using wavelet decomposition. Readers will learn to analyze data in order to emphasize the differences between closely related patterns and then categorize them in a way that is useful to system users.