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Undeclared uranium hitches a ride on cobalt exports from Congo, study says
Philippe (left) and Manzuk quantified the amount of uranium that has been exported from the DRC in cobalt shipments or left behind in the environment. (Photo: Joel Hallberg/UW–Madison)
Researchers at the University of Wisconsin–Madison and Princeton University have published a study in Nature Communications that calls attention to a blind spot in nuclear nonproliferation: The Democratic Republic of the Congo (DRC) has exported thousands of metric tons of uranium, and there is no accounting for where it has gone.
In partnership with Lighthouse Reports and the Financial Times, UW–Madison nuclear engineering professor and nuclear security expert Sébastien Philippe and Ryan Manzuk, a geologist and research fellow in Philippe’s group and at Princeton, conducted the study using countrywide mineralization and geochemical data.
P. Mayo, F. Rodenas, J. M. Campayo, B. Marín, G. Verdú
Nuclear Technology | Volume 175 | Number 1 | July 2011 | Pages 48-52
Technical Paper | Special Issue on the 16th Biennial Topical Meeting of the Radiation Protection and Shielding Division / Radioisotopes | doi.org/10.13182/NT11-A12268
Articles are hosted by Taylor and Francis Online.
The assessment and control of image quality is a fundamental task associated with good practice to guarantee a suitable diagnosis by the radiologist. The need for image quality assessments in radiography is well established, and the use of test phantoms is a common method for this purpose. In this work we present a developed tool that consists of a specific phantom (named RACON) that is used for acceptance and constancy test in order to analyze the image obtained by digital radiographic equipment, software (named SoftRACON) for automated image analysis with digital processing techniques, and a database to store test phantom images and the scoring results.The main objective is to characterize the constancy of the radiographic imaging chain and guarantee acceptable image quality, related to well-functioning of the radiographic equipment. Therefore, the application presented in this work is sensitive enough to the operating conditions of the radiographic digital equipment and allows the assessment of the imaging system quality and, consequently, increases the objectivity (accuracy) in the evaluation of the image.