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Division Spotlight
Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
Meeting Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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A look inside NIST’s work to optimize cancer treatment and radiation dosimetry
In an article just published by the Taking Measure blog of the National Institute of Standards and Technology, Stephen Russek—who leads the Imaging Physics Project in the Magnetic Imaging Group at NIST and codirects the MRI Biomarker Measurement Service—describes his team’s work using phantom stand-ins for human tissue.
Douglas E. Peplow, Kuruvilla Verghese
Nuclear Science and Engineering | Volume 135 | Number 2 | June 2000 | Pages 103-122
Technical Paper | doi.org/10.13182/NSE00-A2128
Articles are hosted by Taylor and Francis Online.
Differential sampling is a powerful tool that allows Monte Carlo to compute derivatives of responses with respect to certain problem parameters. This capability has been implemented within an in-house Monte Carlo code that simulates detailed mammographic images from two new digital systems. Differential sampling allows for the calculation of the first and all second derivatives of all of the different tallies computed by the code as well as the first and second derivatives of the mammographic image itself with respect to material parameters, such as density and cross sections. The theory behind differential sampling is explained, the methodology for implementation into the imaging code is discussed, and two problems are used to demonstrate the power of differential sampling.