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The amount of data being generated today is staggering. And growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming. Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques--including classification, clustering, collaborative filtering, and anomaly detection--to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing. If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis. Familiarize yourself with Spark's programming model and ecosystem Learn general approaches in data science Examine complete implementations that analyze large public datasets Discover which machine learning tools make sense for particular problems Explore code that can be adapted to many uses

Biofluid Mechanics: An Introduction to Fluid Mechanics, Macrocirculation, and Microcirculation, Third Edition shows how fluid mechanics principles can be applied not only to blood circulation, but also to air flow through the lungs, joint lubrication, intraocular fluid movement, renal transport, and other specialty circulations. This new edition contains new homework problems and worked examples, including MATLAB-based examples. In addition, new content has been added on such relevant topics as Womersley and Oscillatory Flows. With advanced topics in the text now denoted for instructor convenience, this book is particularly suitable for both senior and graduate-level courses in biofluids

• 1. What is behavioral neuroscience?
• Part I. Neural foundations of behavior: the basic equipment
• 2. Communication within the nervous system
• 3. The organization and functions of the nervous system
• 4. The methods and ethics of research
• Part II. Motivation and emotion: what makes us go
• 5. Drugs, addiction, and reward
• 6. Motivation and the regulation of internal states
• 7. The biology of sex and gender
• 8. Emotion and health
• Part III. Interacting with the world
• 9. Hearing and language
• 10. Vision and visual perception
• 11. The body senses and movement
• Part IV. Complex behavior
• 12. Learning and memory
• 13. Intelligence and cognitive functioning
• 14. Psychological disorders
• 15. Sleep and consciousness.

Companies looking to move enterprise applications to the cloud are busy weighing several options, such as the use of containers, machine learning, and serverless computing. There's a better way. Instead of helping you fit your use case to individual technologies, this practical guide explains how to use these technologies to fit your use case. Author Rui Costa, a learning consultant with Google, demonstrates this approach by showing you how to run your application on Google Cloud. Each chapter is dedicated to an area of technology that you need to address when planning and deploying your application. This book starts by presenting a detailed fictional use case, followed by chapters that focus on the building blocks necessary to deploy a secure enterprise application successfully. Build serverless applications with Google Cloud Functions Explore use cases for deploying a real-time messaging service Deploy applications to Google Kubernetes Engine (GKE) Build multiregional GKE clusters Integrate continuous integration and continuous delivery with your application Incorporate Google Cloud APIs, including speech-to-text and data loss prevention Enrich data with Google Cloud Dataflow Secure your application with Google Cloud Identity-Aware Proxy Explore BigQuery and visualization with Looker and BigQuery SDKs.

Using an easily accessible, highly templated format, Clinical Cases in Tropical Medicine, 2nd Edition, provides more than 100 realistic scenarios for tropical infectious diseases. Full-color photographs and maps, a convenient question-and-answer presentation, and succinct summary boxes help you identify and understand the tropical diseases you're likely to encounter. This up-to-date 2nd Edition is an excellent resource and study tool for infectious diseases fellows, doctors preparing for exams in tropical medicine, primary care doctors with patients who are global travelers, and global health nurses and practitioners alike. Offers realistic scenarios for encountering patients in rural, resource-poor settings, presenting cases as "unknowns, " just as in a real clinic or emergency situation. Covers newly emerging diseases such as Zika virus, severe fever with thrombocytopenia syndrome (SFTS), and knowlesi malaria. Features topics in migrant medicine of particular importance to clinicians in non-tropical countries, including louse-borne-relapsing fever, spinal brucellosis, and hyperreactive malarial splenomegaly. Includes "classic" tropical diseases such as African trypanosomiasis, chagas, leprosy, and yaws. Reflects the use of novel diagnostics used in resource-poor settings, as well as developing drug resistance in relevant cases. Provides a useful index and map that organize cases geographically, for a targeted approach to study. Serves as a companion to Manson's Tropical Diseases, with a reading list at the end of each case referring to the corresponding chapter in the larger text. Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.
(source: Nielsen Book Data)

• 1. Impacts, adaptation, vulnerability and decision making--
• 2. Global climate models--
• 3. Assessing climate change impacts at the regional scale--
• 4. Dynamical downscaling--
• 5. Empirical-statistical downscaling--
• 6. Added value of downscaling--
• 7. Uncertainty in future projections, and approaches for representing uncertainty--
• 8. Guidance and recommendations for use of (downscaled) climate information--
• 9. The future of regional downscaling-- Index.
• (source: Nielsen Book Data)

Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for policy makers and practitioners interested in climate risk and resilience.
(source: Nielsen Book Data)

• The history and impact of genetics in medicine
• Section A: The scientific basis of human genetics
• The cellular and molecular basis of inheritance
• Chromosomes and cell division
• Finding the cause of monogenic disorders by identifying disease genes
• Laboratory techniques for diagnosis of monogenic disorders
• Patterns of inheritance
• Population and mathematical genetics
• Risk calculation
• Developmental genetics
• Section B: Genetics in medicine and genomic medicine
• Common disease, polygenic and multifactorial genetics
• Screening for genetic disease
• Hemoglobin and the hemoglobinopathies
• Immunogenetics
• The genetics of cancer and cancer genetics
• Pharmacogenetics, precision medicine and the treatment of genetic disease
• Section C: Clinical genetics, counseling, and ethics
• Congenital, abnormalities, dysmorphic syndromes, and learning disability
• Chromosome disorders
• Inborn errors of metabolism
• Mainstream monogenetic disorders
• Prenatal testing and reproductive genetics
• Genetic counseling
• Ethical and legal issues in medical genetics.

Engineering Design, Planning and Management, Second Edition represents a compilation of essential resources, methods, materials and knowledge developed by the author and used over two decades. The book covers engineering design methodology through an interdisciplinary approach, with concise discussions and a visual format. It explores project management and creative design in the context of both established companies and entrepreneurial start-ups. Readers will discover the usefulness of the design process model through practical examples and applications from across engineering disciplines. Sections explain useful design techniques, including concept mapping and weighted decision matrices that are supported with extensive graphics, flowcharts and accompanying interactive templates. Discussions are organized around 12 chapters dealing with topics such design concepts and embodiments, decision-making, finance, budgets, purchasing, bidding, communication, meetings and presentations, reliability and system design, manufacturing design and mechanical design