Universidade Federal de Minas Gerais, Escola de Engenharia - Departamento de Engenharia Nuclear, Programa de Pós-graduação em Ciências e Técnicas Nucleares, Av. Pres. Antônio Carlos 6627, Belo Horizonte MG, Brazil. Electronic address:
Published: April 2023
AI Article Synopsis
Article Abstract
Individual monitoring can provide an estimate of the radioactivity present in the body of the exposed individuals. Periodic monitoring of occupationally exposed individuals is of great importance in case of accidental incorporation. Computational phantoms and Monte Carlo codes are often used to complement the calibration method of counting systems in internal dosimetry. Here, counting efficiency (CE) factors for a WBC system were calculated using MC simulations. The WBC system with a NaI(Tl) detector and the BOMAB phantom was modeled using three MC codes. After validation, the models were used to obtain CE values for a wide range of energies, and a CE curve was generated for the WBC system. To estimate the effects of anatomical differences on the measurement process, two anthropomorphic voxel phantoms were modeled using the VMC code. For the detector position with the highest CE value, the differences when comparing BOMAB results with the MaMP and Yale results were (-1 ± 6)% and (-1 ± 3)%, respectively. The results confirm that the use of the BOMAB phantom is a good approach for the calibration of the whole-body counter system. Measurements should be made at detector position with the highest CE values, and it is recommended to use the mean Monte Carlo CE values calculated in this work.
Purpose: Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized.
Multivariate longitudinal ordinal and continuous data exist in many scientific fields. However, it is a rigorous task to jointly analyse them due to the complicated correlated structures of those mixed data and the lack of a multivariate distribution. The multivariate probit model, assuming there is a multivariate normal latent variable for each multivariate ordinal data, becomes a natural modeling choice for longitudinal ordinal data especially for jointly analysing with longitudinal continuous data.
Heavy metals, nitrate, and nitrite pose significant risks to public health and have raised substantial concern worldwide. This study aimed to investigate the content of nitrate, nitrite, and heavy metals, including Ba, Be, Ca, Fe, K, Li, Mg, Mn, Mo, and Na, in 30 bottled water brands in winter and summer in Tehran, Iran. Heavy metal contents in the samples were analyzed using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), and nitrate and nitrite contents were analyzed using Ion Chromatography (IC).
Purpose: To investigate sensitivity of contributing factors to heterogeneity corrections in ocular brachytherapy using iodine-125 (I) Collaborative Ocular Melanoma Study (COMS) plaques.
Material And Methods: Using egs_brachy, Monte Carlo (MC) simulations were performed for I COMS plaques (model: IsoAid IAI-125A). Homogeneous dose (D) was estimated under the American Association of Physicists in Medicine Task Group-43 assumptions, with 85 Gy prescribed to a 5 mm depth.
Non-invasive glucose monitoring is crucial for diabetes management. This study explores the use of photoacoustic (PA) signals based on optical rotation estimation at multiple depths for detection of glucose concentrations. Experiments were performed with glucose samples mixed in bovine serum albumin with different polarization incidences-vertical (V), 45° linear (P), and right circular (R) polarization.
