Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Radioactive material inspection in public is important to nuclear safety, and it is also the key security for holding large-scale events, while fast and efficient means of detecting radioactive materials are an important technical guarantee for nuclear safety. In this paper, energy and time distribution characteristics information of the natural background and target nuclide gamma particles are used to improve the sequential background comparison method. By using those energy and time distribution characteristics information, with the half-life and characteristic gamma-ray energy and branching ratio information of the nuclide, the response time and the identification accuracy of extremely low radioactive nuclides detected under natural-radiation background can be improved. Based on the theoretical research, the particle event acquisition device with the LaBr(Ce) detector was used to carry out the experimental verification, and the results show that, this method can identify Cs (characteristic energy of 0.662 MeV,8700 Bq,the position relative to the detector is 30 cm) in 6.2 s, and identify Co (characteristic energy of 1.173 MeV and 1.332 MeV, 4500 Bq, the position relative to the detector is 15 cm) in 5.9 s. Experiments prove that the improved background comparison-based sequential Bayesian method can identify low radioactivity radionuclides under natural-radiation background rapidly.
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Source |
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http://dx.doi.org/10.1016/j.apradiso.2022.110596 | DOI Listing |
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