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.
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.
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.
This book is dedicated to the atmosphere of our planet, and discusses historical and contemporary achievements in meteorological science and technology for the betterment of society. The book explores many significant atmospheric phenomena and physical processes from the local to global scale, as well as from the perspective of short and long-term time scales, and links these processes to various applications in other scientific disciplines with linkages to meteorology. In addition to addressing general topics such as climate system dynamics and climate change, the book also discusses atmospheric boundary layer, atmospheric waves, atmospheric chemistry, optics/photometeors, electricity, atmospheric modeling and numeric weather prediction. Through its interdisciplinary approach, the book will be of interest to researchers, students and academics in meteorology and atmospheric science, environmental physics, climate change dynamics, air pollution and human health impacts of atmospheric aerosols.
The Pulitzer Prize-winner’s classic account of the legendary research lab that gave rise to the Digital Age. In the 1970s and ‘80s, Xerox Corporation brought together a brain-trust of engineering geniuses dubbed PARC (Palo Alto Research Center). This brilliant group created several monumental innovations that triggered a technological revolution, including the first personal computer, the laser printer, and the graphical interface (one of the main precursors of the Internet). And when these breakthroughs were rejected by the corporation, these determined inventors turned their ideas into empires that changed the world. Based on extensive interviews with the scientists, engineers, administrators, and executives who lived the story, Dealers of Lightning details PARC’s rise from humble beginnings to a hothouse for ideas. It also shows why Xerox was never able to grasp the cutting-edge innovations PARC delivered. Michael A. Hiltzik offers an unprecedented look at the ideas, the inventions, and the individuals that propelled Xerox PARC to the frontier of techno-history—and the corporate machinations that almost prevented it from achieving greatness.