FRMAC Assessment Manual


Book Description

The ingestion pathway assessment procedures cited in the current version of the ''RMAC Assessment Manual'', DOE/NV/11718-061 (September 1996) have been superseded by new US Food and Drug Administration (FDA) guidance. This addendum replaces the obsolete procedures with a revised set based on the new guidance released by the FDA in August 1998. This addendum provides an overview of the new guidance, revised assessment methods, and assessment aids. It does not provide a general method of ingestion pathway analysis. The scope is limited to that covered by the new guidance titled, ''Accidental Radioactive Contamination of Human Food and Animal Feeds: Recommendations for State and Local Agencies, '' issued by the FDA in August 1998.







FRMAC Operations Manual


Book Description

In the event of a major radiological incident, the Federal Radiological Monitoring and Assessment Center (FRMAC) will coordinate the federal agencies that have various statutory responsibilities. The FRMAC is responsible for coordinating all environmental radiological monitoring, sampling, and assessment activities for the response. This manual describes the FRMAC's response activities in a radiological incident. It also outlines how FRMAC fits in the National Incident Management System (NIMS) under the National Response Framework (NRF) and describes the federal assets and subsequent operational activities which provide federal radiological monitoring and assessment of the affected areas. In the event of a potential or existing major radiological incident, the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Site Office (NNSA/NSO) is responsible for establishing and managing the FRMAC during the initial phases.




The Science of Responding to a Nuclear Reactor Accident


Book Description

The Science of Responding to a Nuclear Reactor Accident summarizes the presentations and discussions of the May 2014 Gilbert W. Beebe Symposium titled "The Science and Response to a Nuclear Reactor Accident". The symposium, dedicated in honor of the distinguished National Cancer Institute radiation epidemiologist who died in 2003, was co-hosted by the Nuclear and Radiation Studies Board of the National Academy of Sciences and the National Cancer Institute. The symposium topic was prompted by the March 2011 accident at the Fukushima Daiichi nuclear power plant that was initiated by the 9.0-magnitude earthquake and tsunami off the northeast coast of Japan. This was the fourth major nuclear accident that has occurred since the beginning of the nuclear age some 60 years ago. The 1957 Windscale accident in the United Kingdom caused by a fire in the reactor, the 1979 Three Mile Island accident in the United States caused by mechanical and human errors, and the 1986 Chernobyl accident in the former Soviet Union caused by a series of human errors during the conduct of a reactor experiment are the other three major accidents. The rarity of nuclear accidents and the limited amount of existing experiences that have been assembled over the decades heightens the importance of learning from the past. This year's symposium promoted discussions among federal, state, academic, research institute, and news media representatives on current scientific knowledge and response plans for nuclear reactor accidents. The Beebe symposium explored how experiences from past nuclear plant accidents can be used to mitigate the consequences of future accidents, if they occur. The Science of Responding to a Nuclear Reactor Accident addresses off-site emergency response and long-term management of the accident consequences; estimating radiation exposures of affected populations; health effects and population monitoring; other radiological consequences; and communication among plant officials, government officials, and the public and the role of the media.




The Book of R


Book Description

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.




Learning Statistics with R


Book Description

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com