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Introduction to Diagnostic Microbiology for the Laboratory Sciences, Second Edition provides a concise study of clinically significant microorganisms for the medical laboratory student and laboratory practitioner.
Inside, you’ll find a wealth of information on important laboratory terminology and the procedures you’ll need to perform to become an effective member of a physician’s office team. Coverage of the advanced procedures performed outside of the physician’s office explains what happens to the samples you send out. There’s also information on CLIA and other government regulations and how they affect each procedure.
The growth and development witnessed today in modern science, engineering, and technology owes a heavy debt to the rare, refractory, and reactive metals group, of which niobium is a member. Extractive Metallurgy of Niobium presents a vivid account of the metal through its comprehensive discussions of properties and applications, resources and resource processing, chemical processing and compound preparation, metal extraction, and refining and consolidation. Typical flow sheets adopted in some leading niobium-producing countries for the beneficiation of various niobium sources are presented, and various chemical processes for producing pure forms of niobium intermediates such as chloride, fluoride, and oxide are discussed. The book also explains how to liberate the metal from its intermediates and describes the physico-chemical principles involved. It is an excellent reference for chemical metallurgists, hydrometallurgists, extraction and process metallurgists, and minerals processors. It is also valuable to a wide variety of scientists, engineers, technologists, and students interested in the topic.
Includes universities, colleges at the 4-year and 2-year or community and junior college levels, technical institutes, and occupationally-oriented vocational schools in the United States and its outlying areas.
Animal disease outbreaks pose many challenges for response authorities that can impact livelihoods, food security, and the environment. Proper disposal of animal carcasses that die or are culled during the outbreak is a key component of a successful response to a disease outbreak because it helps prevent or mitigate the further spread of pathogens and in case of zoonotic disease, to further protect human health. The practical guidelines presented hereby provide carcass and related waste management considerations and recommended procedures for use by Veterinary Services and other official response authorities when developing animal disease outbreak containment and eradication plans. The guidelines apply to animal disease outbreaks of varying sizes, whether the outbreak is isolated to a single premise or spans a region to cover numerous premises. However, they are focused on small to medium-sized holdings in countries without access to engineered landfills, rendering plants or controlled incinerators. The guidelines are written in the spirit of “keep it simple and doable”, considering the limited human and financial resources that many countries are constrained with. Its presentation and practical approach ensure that countries will find it very useful for their emergency operation procedures toolbox. Further, the guidelines directly contribute to the one-health approach by protecting the health of animals, humans, and the environment.
Whether the result of an oil well blowout, vessel collision or grounding, leaking pipeline, or other incident at sea, each marine oil spill will present unique circumstances and challenges. The oil type and properties, location, time of year, duration of spill, water depth, environmental conditions, affected biomes, potential human community impact, and available resources may vary significantly. Also, each spill may be governed by policy guidelines, such as those set forth in the National Response Plan, Regional Response Plans, or Area Contingency Plans. To respond effectively to the specific conditions presented during an oil spill, spill responders have used a variety of response optionsâ€"including mechanical recovery of oil using skimmers and booms, in situ burning of oil, monitored natural attenuation of oil, and dispersion of oil by chemical dispersants. Because each response method has advantages and disadvantages, it is important to understand specific scenarios where a net benefit may be achieved by using a particular tool or combination of tools. This report builds on two previous National Research Council reports on dispersant use to provide a current understanding of the state of science and to inform future marine oil spill response operations. The response to the 2010 Deepwater Horizon spill included an unprecedented use of dispersants via both surface application and subsea injection. The magnitude of the spill stimulated interest and funding for research on oil spill response, and dispersant use in particular. This study assesses the effects and efficacy of dispersants as an oil spill response tool and evaluates trade-offs associated with dispersant use.
Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance