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Static and mobile radiation detectors can be deployed in urban environments for a range of nuclear security applications, including radiological source search-and-tracking scenarios. Modeling detector performance for such applications is challenging, as it does not depend solely on the detector capabilities themselves. Many factors must be taken into consideration, including specific source and background signatures, the topology and constraints of the deployment environment, the presence of nuisance sources, and whether detectors are mobile or static. When considering the simultaneous deployment of multiple, heterogeneous detectors, assessment of the system-wide performance requires the simulation of the individual detectors, and a system-level analysis of the detection performance. In radiological source search-and-tracking scenarios, performance is mostly dominated by the probability of encounter, which depends on the specifics of a given deployment, e.g., static vs. mobile detectors or a combination of both modalities, the number of detectors deployed, the dynamic vs. static setting of false alarm rates, and individual vs. networked operation. The Urban Deployment Model (UDM) toolset was specifically developed to cover the gap in the available generic frameworks for the simulation of radiation detector deployments at city scales. UDM provides a unified and modular framework to support the simulation and performance characterization of heterogeneous detector deployments in urban environments. This paper presents the key components along the UDM workflow.

Introduction: Coding medicinal products described on adverse event (AE) reports to specific entries in standardised drug dictionaries, such as WHODrug Global, is a time-consuming step in case processing activities despite its potential for automation. Many organisations are already partially automating drug coding using text-processing methods and synonym lists, however addressing challenges such as misspellings, abbreviations or ambiguous trade names requires more advanced methods. WHODrug Koda is a drug coding engine using text-processing algorithms, built-in coding rules and machine learning to code drug verbatims to WHODrug Global., Objective: Our aim was to evaluate the drug coding performance of WHODrug Koda on AE reports from VigiBase, the World Health Organization's global database of individual case safety reports, in terms of level of automation and coding quality., Methods: Koda was evaluated on 4.8 million drug entries from VigiBase. Automation level was computed as the proportion of drug entries automatically coded by Koda and was compared to a simple case-insensitive text-matching algorithm. Coding quality was evaluated in terms of coding accuracy, by comparing Koda's prediction to the WHODrug entries found on the AE reports in VigiBase. To better understand the cases in which Koda's coding results did not match with the WHODrug entries in VigiBase, a manual assessment of 600 samples of disagreeing encodings was performed by two teams of expert drug coders., Results: Compared with a simple direct-match baseline, Koda can increase the automation level from 61% to 89%, while providing high coding quality with an accuracy of 97%., Conclusions: Even though Koda was designed for use in clinical trials, Koda achieves automation level and coding quality for drug coding of AE reports comparable with the performance observed in a previous evaluation of Koda on clinical trial data. Koda can thus help organisations to automate their drug coding of AE reports to a large degree., (© 2022. The Author(s).)

Coincidence and time-of-flight measurement techniques are employed to tag fission neutrons emitted from a 252 Cf source sealed on one side with a very thin layer of Au. The source is positioned within a gaseous 4 He scintillator detector. Together with α particles, both light and heavy fission fragments pass through the thin layer of Au and are detected. The fragments enable the corresponding fission neutrons, which are detected in a NE-213 liquid-scintillator detector, to be tagged. The resulting continuous polychromatic beam of tagged neutrons has an energy dependence that agrees qualitatively with expectations. We anticipate that this technique will provide a cost-effective means for the characterization of neutron-detector efficiency in the energy range 1-6MeV., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Untagged gamma-ray and tagged-neutron yields from 241 AmBe and 238 PuBe mixed-field sources have been measured. Gamma-ray spectroscopy measurements from 1 to 5MeV were performed in an open environment using a CeBr 3 detector and the same experimental conditions for both sources. The shapes of the distributions are very similar and agree well with previous data. Tagged-neutron measurements from 2 to 6MeV were performed in a shielded environment using a NE-213 liquid-scintillator detector for the neutrons and a YAP(Ce) detector to tag the 4.44MeVgamma-rays associated with the de-excitation of the first-excited state of 12 C. Again, the same experimental conditions were used for both sources. The shapes of these distributions are also very similar and agree well with previous data, each other, and the ISO recommendation. Our 238 PuBe source provides approximately 2.6 times more 4.44MeVgamma-rays and 2.4 times more neutrons over the tagged-neutron energy range, the latter in reasonable agreement with the original full-spectrum source-calibration measurements performed at the time of their acquisition., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)