We present a bibliometric analysis of the advancements in machine learning for detecting radon nuclear tracks, using publications from 2001 to 2023 sourced from Scopus and Web of Science databases. We analyze the growth in research output, particularly highlighting contributions from China and the United States, and identify key themes such as "machine learning", "radon", "neural networks", and emerging methods like "xgboost" and "long short-term memory networks". Our findings underscore the collaborative efforts within the field, as evidenced by the global authorship networks. The research landscape is mapped out, revealing core and peripheral areas of study that define the current state and prospects of radon detection research. The present study encapsulates the evolution of the field and emphasizes the necessity for continued interdisciplinary collaboration to enhance radon risk asse...

The study investigated the radon emission rate and potential radiological hazards of high-uranium-content building materials in The Ica area of Southwestern Peru. We used a creative technique that combined a closed chamber and active monitor, and it was improved by a hermetic sealing method to maintain secular equilibrium well. The results showed radon emission rates as low as below detection limits (BDL) up to 52.3 mBq/kg·h. Our analyses with a 3' x 3' NaI detector found radionuclide concentrations in cement samples by gamma spectrometry. We found a high positive correlation between radium activity concentration and radon exhalation rate. The activity concentrations of 226Ra, 232Th, and 40K differ significantly, with maximum values reaching 60.6, 22.3, and 1074 mBq/kg·h. We consider these results significant for the safety of materials in the Peruvian construction sector. And we also ...

This study evaluates the effectiveness of advanced statistical and geospatial methods for analyzing radon concentration distributions in indoor environments, using the district of San Martín de Porres, Lima, Peru, as a case study. Radon levels were monitored using LR-115 nuclear track detectors over three distinct measurement periods between 2015 and 2016, with 86 households participating. Detectors were randomly placed in various rooms within each household. Normality tests (Shapiro–Wilk, Anderson–Darling, and Kolmogorov–Smirnov) were applied to assess the fit of radon concentrations to a log-normal distribution. Additionally, analysis of variance (ANOVA) was used to evaluate the influence of environmental and structural factors on radon variability. Non-normally distributed data were normalized using a Box–Cox transformation to improve statistical assumptions, enabling subsequ...

This study evaluates radon exhalation rates and assesses the potential radiological risks of external exposure to primordial radionuclides in building materials employed in the Ica region of Peru, particularly those with high uranium content. The radon exhalation rates are currently measured using a combination of a closed chamber and an active monitor. We proposed a novel method that effectively ensured a hermetic seal for the closed chamber and guaranteed that the efficient maintenance of secular equilibrium. The obtained results ranged from below the detection limit (BDL) to a maximum of 52.3 mBq · kg−1h−1. Gamma spectrometry was employed to measure the concentrations of radionuclides by utilizing a 3′ × 3′ NaI detector. The analysis of cement samples revealed a strong positive correlation between the activity concentration of radium and the radon exhalation rate. The activi...