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Young Members Group
The Young Members Group works to encourage and enable all young professional members to be actively involved in the efforts and endeavors of the Society at all levels (Professional Divisions, ANS Governance, Local Sections, etc.) as they transition from the role of a student to the role of a professional. It sponsors non-technical workshops and meetings that provide professional development and networking opportunities for young professionals, collaborates with other Divisions and Groups in developing technical and non-technical content for topical and national meetings, encourages its members to participate in the activities of the Groups and Divisions that are closely related to their professional interests as well as in their local sections, introduces young members to the rules and governance structure of the Society, and nominates young professionals for awards and leadership opportunities available to members.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Latest News
EPA issues final rule regulating “forever chemicals”
The Environmental Protection Agency announced that it will issue a rule aimed at limiting public exposure to per- and polyfluoroalkyl substances (PFAS). The final rule will designate two widely used PFAS chemicals, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), as hazardous substances under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), also known as Superfund.
According to the EPA, both PFOA and PFOS meet the statutory criteria for designation as hazardous substances.
Dan G. Cacuci, Mihaela Ionescu-Bujor
Nuclear Science and Engineering | Volume 165 | Number 1 | May 2010 | Pages 1-17
Technical Paper | doi.org/10.13182/NSE09-37A
Articles are hosted by Taylor and Francis Online.
When n measurements and/or computations of the same (unknown) quantity yield data points xj with corresponding standard deviations (uncertainties) j such that the distances [vertical bar]xj - xk[vertical bar] between any two data points are smaller than or comparable to the sum (j + k) of their respective uncertainties, the respective data points are considered to be consistent or to agree within error bars. However, when the distances [vertical bar]xj - xk[vertical bar] are larger than (j + k), the respective data are considered to be inconsistent or discrepant. Inconsistencies can be caused by unrecognized or ill-corrected experimental effects (e.g., background corrections, dead time of the counting electronics, instrumental resolution, sample impurities, calibration errors). Although there is a nonzero probability that genuinely discrepant data could occur (for example, for a Gaussian sampling distribution with standard deviation , the probability that two equally precise measurements would be separated by more than 2 is erfc(1) [approximately equal] 0.157), it is much more likely that apparently discrepant data actually indicate the presence of unrecognized errors.This work addresses the treatment of unrecognized errors by applying the maximum entropy principle under quadratic loss, to the discrepant data. Novel results are obtained for the posterior distribution determining the unknown mean value (i.e., unknown location parameter) of the data and also for the marginal posterior distribution of the unrecognized errors. These novel results are considerably more rigorous, are more accurate, and have a wider range of applicability than extant recipes for handling discrepant data.