Presents the current state of the art in lightning science, for advanced undergraduate and graduate students on a single-semester course.

Answers questions about Franklin's experiment, lightning rods, safety considerations, property damage, ball lightning, thunder, and thunderstorms

Absorbing monograph by expert sets forth most of known properties of lightning: cloud and lightning charges, stepped leader, return stroke, dart leader, lightning on other planets, thunder, more. 144 illustrations.

A strong voice emerging from the Black Left.

The Lightning Network (LN) is a rapidly growing second-layer payment protocol that works on top of Bitcoin to provide near-instantaneous transactions between two parties. With this practical guide, authors Andreas M. Antonopoulos, Olaoluwa Osuntokun, and Rene Pickhardt explain how this advancement will enable the next level of scale for Bitcoin, increasing speed and privacy while reducing fees. Ideal for developers, systems architects, investors, and entrepreneurs looking to gain a better understanding of LN, this book demonstrates why experts consider LN a critical solution to Bitcoin's scalability problem. You'll learn how LN has the potential to support far more transactions than today's financial networks. This book examines: How the Lightning Network addresses the challenge of blockchain scaling The Basis of Lightning Technology (BOLT) standards documents The five layers of the Lightning Network Protocol Suite LN basics, including wallets, nodes, and how to operate one Lightning payment channels, onion routing, and gossip protocol Finding paths across payment channels to transport Bitcoin off-chain from sender to recipient

Lightning: Physics and Effects is the first book that covers essentially all aspects of lightning, including lightning physics, lightning protection and the interaction of lightning with a variety of objects and systems as well as with the environment. It is written in a style that will be accessible to the technical non-expert and is addressed to anyone interested in lightning and its effects. This will include physicists, engineers working in the power, communications, computer and aviation industries, meteorologists, atmospheric chemists, foresters, ecologists, physicians working in the area of electrical trauma and architects. This comprehensive reference volume contains over 300 illustrations, 70 tables containing quantitative information and a bibliography of more than 6000 references.

Revised, updated edition of classic work on the physics of lightning covers phenomena, terminology, measurement, photography, spectroscopy, thunder, and more, including reviews of recent research. 140 figures and tables.

"Principles of Lightning Physics presents and discusses the most up-to-date physical concepts that govern many lightning events in nature, including lightning interactions with man-made structures, at a level suitable for researchers, advanced students and well-educated lightning enthusiasts. The author's approach to understanding lightning--to seek out, and show what is common to all lightning flashes--is illustrated by an analysis of each type of lightning and the multitude of lightning-related features. The book examines the work that has gone into the development of new physical concepts, and provides critical evaluations of the existing understanding of the physics of lightning and the lexicon of terms and definitions presently used in lightning research."--Prové de l'editor.

Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch Wrapper Key FeaturesBecome well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domainsSpeed up your research using PyTorch Lightning by creating new loss functions, networks, and architecturesTrain and build new algorithms for massive data using distributed trainingBook Description PyTorch Lightning lets researchers build their own Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize productivity for DL projects while ensuring full flexibility from model formulation through to implementation. You'll take a hands-on approach to implementing PyTorch Lightning models to get up to speed in no time. You'll start by learning how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. Next, you'll build a network and application from scratch and see how you can expand it based on your specific needs, beyond what the framework can provide. The book also demonstrates how to implement out-of-box capabilities to build and train Self-Supervised Learning, semi-supervised learning, and time series models using PyTorch Lightning. As you advance, you'll discover how generative adversarial networks (GANs) work. Finally, you'll work with deployment-ready applications, focusing on faster performance and scaling, model scoring on massive volumes of data, and model debugging. By the end of this PyTorch book, you'll have developed the knowledge and skills necessary to build and deploy your own scalable DL applications using PyTorch Lightning. What you will learnCustomize models that are built for different datasets, model architectures, and optimizersUnderstand how a variety of Deep Learning models from image recognition and time series to GANs, semi-supervised and self-supervised models can be builtUse out-of-the-box model architectures and pre-trained models using transfer learningRun and tune DL models in a multi-GPU environment using mixed-mode precisionsExplore techniques for model scoring on massive workloadsDiscover troubleshooting techniques while debugging DL modelsWho this book is for This deep learning book is for citizen data scientists and expert data scientists transitioning from other frameworks to PyTorch Lightning. This book will also be useful for deep learning researchers who are just getting started with coding for deep learning models using PyTorch Lightning. Working knowledge of Python programming and an intermediate-level understanding of statistics and deep learning fundamentals is expected.

The need to improve the reliability and robustness of power systems and smart grids makes protection of sensitive equipment and power transmission and distribution lines against lightning-related effects a primary concern. Renewable electricity generation capacity has been increasing all over the world, and lightning can cause failures either by hitting the turbines or panels directly or inducing transients on the control systems that lead to equipment failure, malfunction or degradation. This two-volume set assesses how global lightning may respond to global climate change, provides thorough coverage of the lightning phenomenon and its interaction with various objects, and covers methods for the effective protection of structures and systems. It is a valuable reference for researchers in the fields of lightning and power systems, for transmission and distribution line engineers and designers, and is a useful text for related advanced courses. Volume 1 covers fundamentals and modelling of lightning interaction with power systems. This Volume 2 addresses various applications including the application of the Monte Carlo method to lightning protection and insulation coordination practices; lightning interaction with power substations; lightning interaction with power transmission lines; lightning interaction with medium-voltage overhead power distribution systems; lightning interaction with low-voltage overhead power distribution networks; lightning protection of structures and electrical systems inside of buildings; lightning protection of smart grids; lightning protection of wind power systems; lightning protection of photovoltaic systems; measurement of lightning currents and voltages; application of the FDTD method to lightning studies; and software tools for lightning performance assessment.