Assessing Heterogeneity Effects on Points A, B, and Organs at Risk Doses in High-dose-Rate Brachytherapy for Cervical Cancer - A Comparison of 192Ir and 60Co Sources Using Monte Carlo N-Particle 5.

Purpose: The present article deals with investigating the effects of tissue heterogeneity consideration on the dose distribution of 192Ir and 60Co sources in high-dose-rate brachytherapy (HDR-BT). Materials and Methods: A Monte Carlo N-Particle 5 (MCNP5) code was developed for the simulation of the dose distribution in homogeneous and heterogeneous phantoms for cervical cancer patients. The phantoms represented water-equivalent and human body-equivalent tissues. Treatment data for a patient undergoing HDR-BT with a 192Ir source were used as a reference for validation, and for 60Co, AAPM Task Group 43 methodology was also applied. The dose values were calculated for both source types in the phantoms. Results: The results showed a good agreement between the calculated dose in the homogeneous phantom and the real patient's treatment data, with a relative difference of less than 5% for both sources. However, when comparing the absorbed doses at critical points such as Point A right, Point A left, Point B right, Point B left, bladder International Commission on Radiation Units and Measurement (ICRU) point, and recto-vaginal ICRU point, the study revealed significant percentage differences (approximately 5.85% to 12.02%) between the homogeneous and heterogeneous setups for both 192Ir and 60Co sources. The analysis of dose-volume histograms (DVH) indicated that organs at risk, notably the rectum and bladder, still received doses within recommended limits. Conclusions: The study concludes that 60Co and 192Ir sources can be effectively used in HDR-BT, provided that careful consideration is given to tissue heterogeneity effects during treatment planning to ensure optimal therapeutic outcomes.

Interest in antibiotic pharmacokinetic modelling in the context of optimising dosing and reducing resistance: bibliometric analysis.

INTRODUCTION: In the era of problems with resistant bacteria strains, pharmacokinetic (PK) modelling offers ways to optimise antibiotic therapy and minimise the risk of resistance development. This bibliometric study aimed to investigate trends in PK modelling stu-dies. The goal was to provide researchers with comprehensive insight and identify future needs. MATERIAL AND METHODS: We used Bibliometrix, VOSviewer, and CiteSpace to analyse Web of Science articles on antibiotic PK modelling from 1983 to March 2023. RESULTS: We analysed 968 papers following the inclusion criteria and built a keywords co-occurrence map and timeline. The average annual growth rate of subject-related publications was 35.56% between 1983 and 2022, maintaining a continuous upward trend. Roberts J.A., Lipman J., and Wallis S.C. are the three most productive and impactful authors (82, 57, 34 articles, and h-index of 30, 25, 15, respectively). The United States leads in this field of research (29.13% of papers). The most relevant affiliations are the University of Queensland, Royal Brisbane and Women's Hospital, and Monash University. The top three most productive and impactful journals are Antimicrobial Agents and Chemotherapy, Journal of Antimicrobial Chemotherapy, and International Journal of Antimicrobial Agents (181, 83, 47 articles and h-index of 42, 30, 18, respectively). Most articles by keyword clustered on meropenem, vancomycin, and amikacin. Moreover, therapeutic drug monitoring, resistance, antibiotic dosing, target attainment, the intensive care unit, and paediatrics are the most trending aspects. CONCLUSIONS: Given the results of this study, we expect to see a steady increase in interest in exploiting the potential of PK modelling for optimising antibiotic therapy.

Exploring white matter dynamics and morphology through interactive numerical phantoms: the White Matter Generator.

Brain white matter is a dynamic environment that continuously adapts and reorganizes in response to stimuli and pathological changes. Glial cells, especially, play a key role in tissue repair, inflammation modulation, and neural recovery. The movements of glial cells and changes in their concentrations can influence the surrounding axon morphology. We introduce the White Matter Generator (WMG) tool to enable the study of how axon morphology is influenced through such dynamical processes, and how this, in turn, influences the diffusion-weighted MRI signal. This is made possible by allowing interactive changes to the configuration of the phantom generation throughout the optimization process. The phantoms can consist of myelinated axons, unmyelinated axons, and cell clusters, separated by extra-cellular space. Due to morphological flexibility and computational advantages during the optimization, the tool uses ellipsoids as building blocks for all structures; chains of ellipsoids for axons, and individual ellipsoids for cell clusters. After optimization, the ellipsoid representation can be converted to a mesh representation which can be employed in Monte-Carlo diffusion simulations. This offers an effective method for evaluating tissue microstructure models for diffusion-weighted MRI in controlled bio-mimicking white matter environments. Hence, the WMG offers valuable insights into white matter's adaptive nature and implications for diffusion-weighted MRI microstructure models, and thereby holds the potential to advance clinical diagnosis, treatment, and rehabilitation strategies for various neurological disorders and injuries.

Background radioactivity level estimation and passive shield optimization using adjoint Monte Carlo method.

The current study proposes a procedure to estimate the activity concentration of natural radionuclides and to optimize passive shielding solutions for HPGe detectors using adjoint Monte Carlo (MC) simulation technique of Geant4 for the first time. The background spectrum is acquired for 1.56 × 106 s using an HPGe detector model (GC3020), set inside a shielding solution, during 2021-2022 to estimate the activity concentration of natural radionuclides inside the shielding. While, a background spectrum for 65,000 s is acquired with shielding removed to estimate the concentration of natural radionuclides in the building materials of the laboratory. The detector design used in the simulations is validated by comparing computed and measured Full Energy Peak Efficiency (FEPE) for point sources 241Am, 152Eu, 137Cs, 133Ba, and 60Co. Adjoint MC simulations are used to compute the activity concentration of natural radionuclides assuming an isotropic distribution. The activity concentration of 40K, 226Ra and 232Th in the building material is found to be 524 ± 140, 83 ± 20 and 65 ± 18 Bqkg-1, respectively. The computed values are found in good agreement with the published data. The natural radioactivity levels of 40K, 226Ra and 232Th measured in lead shielding are 155.7 ± 0.1 mBqkg-1, 24 ± 13 mBqkg-1 and 33 ± 17 mBqkg-1 respectively. The radiological risks arising due to natural radioactivity is assessed by calculating radium equivalent activity (Raeq), indoor radiation hazard index (Hin) and annual effective dose equivalent. All the radiological parameters are found below their permissible limits and building materials may be considered radiologically safe. The optimal lead shield thickness for the detector is determined to be 12 cm, resulting in reduction of background signal by two orders of magnitude compared to an unshielded detector. The adjoint MC simulations in Geant4 are 103-104 times more rapid as compared to normal simulations for shield optimization of HPGe detectors and therefore, are identified as viable computing solution to calculate the activity of the background radiation.

Insights of infected Schwann cells extinction and inherited randomness in a stochastic model of leprosy.

Investigating disease progression, transmission of infection and impacts of Multidrug Therapy (MDT) to inhibit demyelination in leprosy involves a certain amount of difficulty in terms of the in-built uncertain complicated and complex intracellular cell dynamical interactions. To tackle this scenario and to elucidate a more realistic, rationalistic approach of examining the infection mechanism and associated drug therapeutic interventions, we propose a four-dimensional ordinary differential equation-based model. Stochastic processes has been employed on this deterministic system by formulating the Kolmogorov forward equation introducing a transition state and the quasi-stationary distribution, exact distribution analysis have been investigated which allow us to estimate an expected time to extinction of the infected Schwann cells into the human body more prominently. Additionally, to explore the impact of uncertainty in the key intracellular factors, the stochastic system is investigated incorporating random perturbations and environmental noises in the disease dissemination, proliferation and reinfection rates. Rigorous numerical simulations validating the analytical outcomes provide us significant novel insights on the progression of leprosy and unravelling the existing major treatment complexities. Analytical experiments along with the simulations utilizing Monte-Carlo method and Euler-Maruyama scheme involving stochasticity predicts that the bacterial density is underestimated due to the recurrence of infection and suggests that maintaining a drug-efficacy rate in the range 0.6-0.8 would be substantially efficacious in eradicating leprosy.

Exotic phases induced by RKKY interaction in the square lattice.

We study a model of Ising spins in which direct exchange interactions compete with the Ruderman-Kittel-Kasuya-Yosida (RKKY) coupling, which may arise effectively from itinerant electrons. We consider the model in the two-dimensional square lattice and focus on values of the RKKY coupling constant (JRKKY) and the Fermi momentum (kF) that induce strong frustration. We study the low-temperature magnetic field phase diagram using Monte Carlo simulations, considering several nearest neighbors in the RKKY interaction. Magnetic frustration yields a rich phase diagram with a variety of exotic phases. We compute the structure factors and define appropriate order parameters to describe the transitions. We also discuss the validity of the approximation made for long-range couplings and analytically demonstrate the change in the coexistence lines in the phase diagram by including up to the tenth nearest neighbors.

The determination of coefficients for size specific effective dose for adult and pediatric patients undergoing routine computed tomography examinations.

The effective dose resulting from computed tomography (CT) scans provides an assessment of the risk associated with stochastic effects but does not account for the patient's size. Advances in Monte Carlo simulations offer the potential to obtain organ dose data from phantoms of varying stature, enabling derivation of a size-specific effective doses (SEDs) representing doses to individual patients. This study aimed to compute size-specific k-conversion factors for SED in routine CT examinations for adult and pediatric patients of different sizes. Radiation interactions were simulated for adult and pediatric phantom models of various sizes using National Cancer Institute CT version 3.0.20211123. Subsequent calculations of SED were performed, and coefficients for SED were derived, considering the variations in body sizes. The results revealed a strong correlation between effective diameter and weight, observed with size-specific k-conversion factors for adult and pediatric phantoms, respectively. While size-specific k-conversion factors for CT brain remained constant in adults, values for pediatric cases varied. When using the tube current modulation (TCM) system, size-specific k-conversion factors increased in larger phantoms and decreased in smaller ones. The extent of this increase or decrease correlated with the set TCM strength. This study provides coefficients for estimating SEDs in routine CT exams. Software utilizing look-up tables of coefficients can be used to provide dose information for CT scanners at local hospitals, offering guidance to practitioners on doses to individual patients and improving radiation risk awareness in clinical practice.

Corrigendum: Comparison of 3DCRT and IMRT out-of-field doses in pediatric patients using Monte Carlo simulations with treatment planning system calculations and measurements.

[This corrects the article DOI: 10.3389/fonc.2022.879167.].

Theoretical model of donor-donor and donor-acceptor energy transfer on a nanosphere.

In this study, we introduce a novel advancement in the field of theoretical exploration. Specifically, we investigate the transfer and trapping of electronic excitations within a two-component disordered system confined to a finite volume. The implications of our research extend to energy transfer phenomena on spherical nanoparticles, characterized by randomly distributed donors and acceptors on their surface. Utilizing the three-body Padé approximant technique, previously employed in single-component systems, we apply it to address the challenge of trapping within our system. To validate the robustness of our model, we conduct Monte Carlo simulations on a donor-acceptor system positioned on a spherical nanoparticle. In particular, very good agreement between the model and Monte Carlo simulations has been found for donor fluorescence intensity decay.

Intrinsic dynamics of emulsions: Experiments in microgravity on the International Space Station.

HYPOTHESIS: In order to understand the basic mechanisms affecting emulsion stability, the intrinsic dynamics of the drop population must be investigated. We hypothesize that transient ballistic motion can serve as a marker of interactions between drops. In 1G conditions, buoyancy-induced drop motion obscures these interactions. The microgravity condition onboard the International Space Station enable this investigation. EXPERIMENTS: We performed Diffusing Wave Spectroscopy (DWS) experiments in the ESA Soft Matter Dynamics (SMD) facility. We used Monte Carlo simulations of photon trajectory to support data analysis. The analysis framework was validated by ground-based characterizations of the initial drop size distribution (DSD) and the properties of the oil/water interface in the presence of surfactant. FINDINGS: We characterized the drop size distribution and found to be bi-disperse. Drop dynamics shows transient ballistic features at early times, reaching a stationary regime of primarily diffusion-dominated motion. This suggests different ageing mechanisms: immediately after emulsification, the main mechanism is coalescence or aggregation between small drops. However at later times, ageing proceeds via coalescence or aggregation of small with large drops in some emulsions. Our results elucidate new processes relevant to emulsion stability with potential impact on industrial processes on Earth, as well as enabling technologies for space exploration.

Molecular Insights into Adhesion at Interface of Geopolymer Binder and Cement Mortar.

The degradation of concrete and reinforced concrete structures is a significant technical and economic challenge, requiring continuous repair and rehabilitation throughout their service life. Geopolymers (GPs), known for their high mechanical strength, low shrinkage, and durability, are being increasingly considered as alternatives to traditional repair materials. However, there is currently a lack of understanding regarding the interface bond properties between new geopolymer layers and old concrete substrates. In this paper, using advanced computational techniques, including quantum mechanical calculations and stochastic modeling, we explored the adsorption behavior and interaction mechanism of aluminosilicate oligomers with different Si/Al ratios forming the geopolymer gel structure and calcium silicate hydrate as the substrate at the interface bond region. We analyzed the electron density distributions of the highest occupied and lowest unoccupied molecular orbitals, examined the reactivity indices based on electron density functional theory, performed Mulliken charge population analysis, and evaluated global reactivity descriptors for the considered oligomers. The results elucidate the mechanisms of local and global reactivity of the oligomers, the equilibrium low-energy configurations of the oligomer structures adsorbed on the surface of C-(A)-S-H(I) (100), and their adsorption energies. These findings contribute to a better understanding of the adhesion properties of geopolymers and their potential as effective repair materials.

Transfer functions forQA/QBinternational regulatory limits for the safe transport of radioactive materials.

This paper presents a proposed revision of the International Atomic Energy Agency transport regulations, related to theA1andA2limit values used to determine the radioactive transport classification. Based on the 'Qsystem', a novel methodology was introduced to deriveQAandQBvalues related to scenarios involving external exposure from a distant source. These values are key parameters that respectively represent the total effective dose and total equivalent dose to the skin, from all primary and secondary particles contributing to radiation exposure. The International Working Group (WGA1/A2) is established and associated with the TRANSSC Technical Expert Group on Radiation Protection. A review of theA1andA2values is performed in response to identified limitations within the existingQsystem. The followed approach is based on Monte Carlo simulations that enabled the development of transfer functions aimed at reducing computational time and increasing the flexibility of dose evaluations for any radionuclide with known particle emission spectra. This method allows updating theQAandQBvalues to account for future data evolutions (decay data, fluence-to-dose conversion coefficients) and standardizing the calculation of regulation limits across all referenced radionuclides and scenarios related to external exposure. The transfer functions are established using three Monte Carlo simulation codes-FLUKA, Geant4, and MCNP-and address the previous limitations of the 'Qsystem', reflecting the latest International Commission for Radiation Protection recommendations and improvements in calculation techniques. The results of the WG show consistent agreement across the codes, with minor discrepancies observed at low primary energies due to statistical uncertainties and different handling of stopping power for electrons/positrons in the codes. This revised approach aligns with current standards and recommendations, ensuring that the radiological consequences of transport accidents are acceptable for the newA1andA2limits from a radiological protection perspective.

Preclinical photon minibeam radiotherapy using a custom collimator: Dosimetry characterization and preliminary in-vivo results on a glioma model.

PURPOSE: The purpose of this study is to investigate the dosimetric characteristics of a collimator for minibeam radiotherapy (MBRT) with film dosimetry and Monte Carlo (MC) simulations. The outcome of MBRT with respect to conventional RT using a glioma preclinical model was also evaluated. METHODS: A multi-slit collimator was designed to be used with commercial small animal irradiator. The collimator was built by aligning 0.6 mm wide and 5 mm thick parallel lead leaves at 0.4 mm intervals. Dosimetry characteristics were evaluated by Gafchromic (CG) films and TOPAS Monte Carlo (MC) code. An in vivo experiment was performed using a glioma preclinical model by injecting two million GL261cells subcutaneously and treating with 25 Gy, single fraction, with MBRT and conventional RT. Survival curves and acute radiation damage were measured to compare both treatments. RESULTS: A satisfactory agreement between experimental results and MC simulations were obtained, the measured FWHM and distance between the peaks were respectively 0.431 and 1.098 mm. In vivo results show that MBRT can provide local tumor control for three weeks after RT treatment and a similar survival fraction of open beam radiotherapy. No severe acute effects were seen for the MBRT group. CONCLUSIONS: We developed a minibeam collimator and presented its dosimetric features. Satisfactory agreement between MC and GC films was found with differences consistent with uncertainties due to fabrication and set-up errors. The survival curves of MBRT and open field RT are similar while atoxicity is dramatically lower with MBRT, preliminarily confirming the expected effect.

Trace elements in the Upper Indus River Basin (UIRB) of Western Himalayas: Quantification, sources modeling, and impacts.

This study conducted a comprehensive analysis of trace element concentrations in the Upper Indus River Basin (UIRB), a glacier-fed region in the Western Himalayas (WH), aiming to discern their environmental and anthropogenic sources and implications. Despite limited prior data, 69 samples were collected in 2019 from diverse sources within the UIRB, including mainstream, tributaries, and groundwater, to assess trace element concentrations. Enrichment factor (EF) results and comparisons with regional and global averages suggest that rising levels of Zn, Cd, and As may pose safety concerns for drinking water quality. Advanced multivariate statistical techniques such as principal component analysis (PCA), absolute principal component scores (APCS-MLR), Monte Carlo simulation (MCS), etc were applied to estimate the associated human health hazards and also identified key sources of trace elements. The 95th percentile of the MCS results indicates that the estimated total cancer risk for children is significantly greater than (>1000 times) the USEPA's acceptable risk threshold of 1.0 × 10-6. The results classified most of the trace elements into two distinct groups: Group A (Li, Rb, Sr, U, Cs, V, Ni, TI, Sb, Mo, Ge), linked to geogenic sources, showed lower concentrations in the lower-middle river reaches, including tributaries and downstream regions. Group B (Pb, Nb, Cr, Zn, Be, Al, Th, Ga, Cu, Co), influenced by both geogenic and anthropogenic activities, exhibited higher concentrations near urban centers and midstream areas, aligning with increased municipal waste and agricultural activities. Furthermore, APCS-MLR source apportionment indicated that trace elements originated from natural geogenic processes, including rock-water interactions and mineral dissolution, as well as anthropogenic activities. These findings underscore the need for targeted measures to mitigate anthropogenic impacts and safeguard water resources for communities along the IRB and WH.

Noise-reduction techniques for 1H-FID-MRSI at 14.1 T: Monte Carlo validation and in vivo application.

Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high resolution over the entire brain. The constant demand for higher spatial resolution in 1H-MRSI has led to increased interest in post-processing-based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise-reduction techniques, Marchenko-Pastur principal component analysis (MP-PCA) based denoising and low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential with and impact on preclinical 14.1 T fast in vivo 1H-FID-MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise-reduction strategies were conducted using Monte Carlo simulations. Results showed that both denoising techniques increased the apparent signal-to-noise ratio (SNR) while preserving noise properties in each spectrum for both in vivo and Monte Carlo datasets. Relative metabolite concentrations were not significantly altered by either method and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted for lower-concentration metabolites. Our study provided a framework for how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1H-FID MRSI data at 14.1 T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care, especially for low-concentration metabolites.

Biswas-Chatterjee-Sen Model on Solomon Networks with Two Three-Dimensional Lattices.

The Biswas-Chatterjee-Sen (BChS) model of opinion dynamics has been studied on three-dimensional Solomon networks by means of extensive Monte Carlo simulations. Finite-size scaling relations for different lattice sizes have been used in order to obtain the relevant quantities of the system in the thermodynamic limit. From the simulation data it is clear that the BChS model undergoes a second-order phase transition. At the transition point, the critical exponents describing the behavior of the order parameter, the corresponding order parameter susceptibility, and the correlation length, have been evaluated. From the values obtained for these critical exponents one can confidently conclude that the BChS model in three dimensions is in a different universality class to the respective model defined on one- and two-dimensional Solomon networks, as well as in a different universality class as the usual Ising model on the same networks.

Modelling the colony growth dynamics of Listeria monocytogenes single cells after exposure to peracetic acid and acidic conditions.

Studies of classical microbiology rely on the average behaviour of large cell populations without considering that clonal bacterial populations may bifurcate into phenotypic distinct sub-populations by random switching mechanisms.Listeria monocytogenes exposure to sublethal stresses may induce different physiological states that co-exist (i.e., sublethal injury or dormancy) and present variable resuscitation capacity. Exposures to peracetic acid (PAA; 10-30 ppm; for 3 h), acetic acid and hydrochloric acid (AA and HCl; pH 3.0-2.5; for 5 h) at 20 °C were used to induce different physiological states in L. monocytogenes, Scott A strain. After stress exposure, colony growth of single cells was monitored, on Tryptic Soy Agar supplemented with 0.6 % Yeast Extract, using time-lapse microscopy, at 37 °C. Images were acquired every 5 min and were analyzed using BaSCA framework. Most of the obtained growth curves of the colonies were fitted to the model of Baranyi and Roberts for the estimation of lag time (λ) and maximum specific growth rate (µmax), except the ones obtained after exposure to AA pH 2.7 and 2.5 that were fitted to the Trilinear model. The data of λ and µmax that followed a multivariate normal distribution were used to predict growth variability using Monte Carlo simulations. Outgrowth kinetics after treatment with AA (pH 2.7 and 2.5; for 5 h at 20 °C), PAA (30 ppm; for 3 h at 20 °C) revealed that these stress conditions increase the skewness of the variability distributions to the right, meaning that the variability in lag times increases in favour of longer outgrowth. Exposures to AA pH 2.5 and 30 ppm PAA resulted in two distinct subpopulations per generation with different growth dynamics. This switching mechanism may have evolved as a survival strategy for L. monocytogenes cells, maximizing the chances of survival. Simulation of microbial growth showed that heterogeneity in growth dynamics is increased when cells are recovering from exposure to sublethal stresses (i.e. PAA and acidic conditions) that may induce injury or dormancy.

Using Monte Carlo Simulation to Forecast the Scientific Utility of Psychological App Studies: A Tutorial.

Mobile applications offer a wide range of opportunities for psychological data collection, such as increased ecological validity and greater acceptance by participants compared to traditional laboratory studies. However, app-based psychological data also pose data-analytic challenges because of the complexities introduced by missingness and interdependence of observations. Consequently, researchers must weigh the advantages and disadvantages of app-based data collection to decide on the scientific utility of their proposed app study. For instance, some studies might only be worthwhile if they provide adequate statistical power. However, the complexity of app data forestalls the use of simple analytic formulas to estimate properties such as power. In this paper, we demonstrate how Monte Carlo simulations can be used to investigate the impact of app usage behavior on the utility of app-based psychological data. We introduce a set of questions to guide simulation implementation and showcase how we answered them for the simulation in the context of the guessing game app Who Knows (Rau et al., 2023). Finally, we give a brief overview of the simulation results and the conclusions we have drawn from them for real-world data generation. Our results can serve as an example of how to use a simulation approach for planning real-world app-based data collection.

Investigations on the beam quality correction factor for ionization chambers in high-energy brachytherapy dosimetry.

Objective. To enhance the investigations on MC calculated beam quality correction factors of thimble ionization chambers from high-energy brachytherapy sources and to develop reliable reference conditions in source and detector setups in water.Approach. The response of five different ionization chambers from PTW-Freiburg and Standard Imaging was investigated for irradiation by a high dose rate Ir-192 Flexisource in water. For a setup in a Beamscan water phantom, Monte Carlo simulations were performed to calculate correction factors for the chamber readings. After exact positioning of source and detector the absorbed dose rate at the TG-43 reference point at one centimeter nominal distance from the source was measured using these factors and compared to the specification of the calibration certificate. The Monte Carlo calculations were performed using the restricted cema formalism to gain further insight into the chamber response. Calculations were performed for the sensitive volume of the chambers, determined by the methods currently used in investigations of dosimetry in magnetic fields.Main results. Measured dose rates and values from the calibration certificate agreed within the combined uncertainty (k= 2) for all chambers except for one case in which the full air cavity was simulated. The chambers showed a distinct directional dependence. With the restricted cema formalism calculations it was possible to examine volume averaging and energy dependence of the perturbation factors contributing to the beam quality correction factor also differential in energy.Significance. This work determined beam quality correction factors to measure the absorbed dose rate from a brachytherapy source in terms of absorbed dose to water for a variety of ionization chambers. For the accurate dosimetry of brachytherapy sources with ionization chambers it is advisable to use correction factors based on the sensitive volume of the chambers and to take account for the directional dependence of chamber response.

Renewing Interest in Zeolites as Adsorbents for Capture of Cationic Dyes from Aqueous and Ethanolic Solutions: A Simulation-Based Insight into the Efficiency of Dye Adsorption in View of Wastewater Treatment and Valorization of Post-Sorption Materials.

The impact of solvents on the efficiency of cationic dye adsorption from a solution onto protonated Faujasite-type zeolite (FAU-Y) was investigated in the prospect of supporting potential applications in wastewater treatment or in the preparation of building blocks for optical devices. The adsorption isotherms were experimentally determined for methylene blue (MB) and auramine O (AO) from single-component solutions in water and in ethanol. The limiting dye uptake (saturation capacity) was evaluated for each adsorption system, and it decreased in the order of MB-water > AO-water > AO-ethanol > MB-ethanol. The mutual distances and orientations of the adsorbed dye species, and their interactions with the oxygen sites of the FAU-Y framework, with the solvent molecules, and among themselves were inferred from Monte Carlo simulations and subsequently utilized to rationalize the observed differences in the saturation capacity. The dye-solvent competition and the propensity of the dyes to form compact pi-stacked dimers were shown to play an important role in establishing a non-uniform distribution of the adsorbed species throughout the porous space. The two effects appeared particularly strong in the case of the MB-water system. The necessity of including solvent effects in modeling studies is emphasized.