Combined experimental and Monte Carlo verification of 137Cs brachytherapy plans for vaginal applicators

Dose rates in a phantom around a shielded and an unshielded vaginal applicator containing Selectron low-dose-rate 137Cs sources were determined by experiment and Monte Carlo simulation. Measurements were performed with thermoluminescent dosimeters in a white polystyrene phantom using an experimental protocol geared for precision. Calculations for the same set-up were done using a version of the EGS4 Monte Carlo code system modified for brachytherapy applications into which a new combinatorial geometry package developed by Bielajew was recently incorporated. Measured dose rates agree with Monte Carlo estimates to within 5% (1 SD) for the unshielded applicator, while highlighting some experimental uncertainties for the shielded applicator. Monte Carlo calculations were also done to determine a value for the effective transmission of the shield required for clinical treatment planning, and to estimate the dose rate in water at points in axial and sagittal planes transecting the shielded applicator. Comparison with dose rates generated by the planning system indicates that agreement is better than 5% (1 SD) at most positions. The precision thermoluminescent dosimetry protocol and modified Monte Carlo code are effective complementary tools for brachytherapy applicator dosimetry.     

Developing a model of DNA replication to be used for Monte Carlo calculations that predict the sizes and shapes of molecules resulting from DNA double-strand breaks induced by X irradiation during DNA synthesis

A Monte Carlo computer program was written to introduce double-strand breaks (DSBs) randomly into cellular DNA that is configured according to different models of DNA replication. Then, from a review of the literature using DNA fiber autoradiography and other studies relating to rates of replication of DNA that is organized in approximately 3-Mbp regions or bands, a particular model for DNA replication was developed. Using this model, Monte Carlo calculations were made to predict the types and sizes of molecules that would result from introducing DSBs into DNA when synchronous cells are irradiated in the middle of S phase. Then results of the Monte Carlo calculations were compared with migration profiles obtained by pulsed-field gel electrophoresis (PFGE) for molecular size distributions of linear DNA molecules. For these comparisons, CHO cells irradiated in S phase also were pulse-labeled at the time of irradiation with [3H]dThd for 15 min to compare the migration patterns of 3H-labeled replicating DNA with those of the mass of S-phase DNA, measured by imaging with a CCD camera. For the Monte Carlo calculations, we assumed from the reports in the literature that molecules containing replication bubbles with and without forks would be trapped in the PFGE plug. We also assumed that those molecules that are < or = 8 Mbp, both linear and with replication forks, would be released into the lane. However, approximately 75% of the 3H-labeled DNA that is released from the plug migrated much more slowly than linear molecules, which we attributed to the slow migration of 3H-labeled molecules having replication forks not attached to bubbles. The percentages of both mass of S-phase DNA and 3H-labeled replicating DNA released from the plug, as determined by PFGE, were compared with comparable values determined from Monte Carlo calculations. A DNA replication model that provides good agreement between the PFGE results and Monte Carlo calculations is described. Furthermore, Monte Carlo methodology is presented that can be used for comparing data obtained with PFGE with results of Monte Carlo calculations that are based on different models of DNA replication and different assumptions for the migration of various types of replicating molecules.     

Mechanistic modeling of prokaryotic mRNA decay

A mechanistic model of gene expression was developed to test three prevailing and sliding prokaryotic mRNA decay theories: ribosome protection of mRNA from endonucleases, 5' binding and sliding of endonucleases on mRNA, and hybrid 5' binding/ribosome protection. The discrete event simulation incorporates the molecular events that determine both cellular mRNA and protein levels. A Monte Carlo technique was used to approximate the inherent randomness of the molecular processes involved in gene expression. Each of the decay theories was tested for the ability to predict the effects of ribosome loading and translation rate on mRNA stability as well as the observed 5' to 3' directionality of mRNA decay. The modeling results show that the hybrid decay mechanism best predicts the experimentally-observed mRNA decay behaviors. The 5' binding mechanism fails to adequately predict the sensitivity of mRNA stability to changes in translation rate and ribosome loading, while the ribosome protection mechanism does not correctly predict 5' to 3' decay directionality. In addition to discriminating between the three decay theories, the simulations provide insights into hybrid decay mechanism specific details such as RNase binding and cleavage characteristics. Finally, we discuss the application of the current mechanistic model for analysing and predicting expression from more complex genetic systems.     

Linearized inverse Monte Carlo method applied to Ni3Fe

Atomic interaction potentials in f.c.c. ordering systems are deduced from short range order measurements above the ordering temperature T_c. This “Linearized Inverse Monte Carlo Method” is applied to the Ni₃Fe system. In this case, it is shown that 4 potentials can explain the short range order measured at a given temperature. The precision of the results is discussed and it is shown that the four determined potentials are strongly correlated.     

Assessing Local Structure in PbZn1/3Nb2/3O3 Using Diffuse Scattering and Reverse Monte Carlo Refinement

We use an extensive X-ray diffuse scattering dataset collected from the relaxor ferroelectric PbZn_1/3Nb_2/3O₃ to study the feasibility of refining a nanoscale structure with the reverse Monte Carlo method. Six integer and non-integer reciprocal sections are used with a total number of nearly 10⁵ symmetry-independent data points. Very good agreement between observed and calculated diffuse scattering patterns is achieved with rather subtle diffuse intensity modulations being satisfactorily reproduced. The correlations within the refined local structure are related to the possible physical mechanisms behind them. We discuss the ambiguity of the obtained results and feasible constraining schemes.     

Detection of trisomy 3 in primary gastric B-cell lymphoma by using chromosome in situ hybridization on paraffin sections

Recently, new backscatter factors for low-energy x rays derived from Monte Carlo calculations have been recommended in the UK code of practice for kilovoltage dosimetry published by (IPEMB). As these data, presented as a function of half-value layer, do not take account of the variation of the x-ray spectra for a given HVL, we have undertaken an experimental study in order to determine BSG for the beam qualities provided by a Darpac 2000 therapy unit. A RTL detector such as Li2B4O7:Cu and parallel-plate ion chambers specially designed for low-energy x-ray dosimetry have been used. The results obtained show very good agreement between the TLD and the Monte Carlo calculations, confirming values obtained by other authors with lithium borate TLD. On the contrary, the results obtained with plane-parallel ion chambers show discrepancies up to 9% that are discussed.     

Neural Network Embedded Monte Carlo Approach for Water Quality Modeling under Input Information Uncertainty

This paper proposes a neural network embedded Monte Carlo (NNMC) approach to account for uncertainty in water quality modeling. The framework of the proposed method has three major parts: a numerical water quality model, a neural network technique, and Monte Carlo simulation. The numerical model is used to generate desirable output for training and testing sets, and the neural network is used as a universal functional mapping tool to approximate the input-output response of the numerical model. The Monte Carlo simulation then uses the neural network to generate numerical realizations based on a probabilistic distribution of parameters, thus obtaining a probabilistic distribution of the simulated state variables. By embedding a neural network into the conventional Monte Carlo simulation, the proposed approach significantly improves upon the conventional method in computational efficiency. The proposed approach has been applied to uncertainty and risk analyses of a phosphorus model for Triadelphia Reservoir in Maryland. The results of this research show that the NNMC approach has potential for efficient uncertainty analysis of water quality modeling.     

Comparison of Risk Calculation Methods for a Culvert

A comparative study of eight different risk calculation methods has been performed on the occurrence probability of inadequate capacity of a culvert to pass floods. The five basic risk calculation methods used in this study are the mean-value first-order second-moment method, advanced first-order second-moment method, point estimate method, Latin hypercube sampling method, and Monte Carlo simulation. Two options each for the point estimation and Monte Carlo methods are also investigated. Building upon the first four basic calculation methods, three additional methods are suggested. They are the first-order second-moment mixed mode method, generalized mixed mode method, and significant component method. Within each of the first four basic methods risks are calculated, whenever possible, using two definitions of failure parameter, i.e., (1) the performance function Z directly as a function of all the contributing variables; and (2) separate calculations of loading and resistance (capacity). Logic trees are presented to illustrate possible causes of culvert failure, the ways to account for component factors such as those from hydraulics and hydrology and to combine the component risks for total risk. Risk of inadequate flow capacity for a five-foot diameter culvert is evaluated as an example. Three sets of uncertainty data for the random variables are used; the first set data is adopted from a study in the literature, in which uncertainties from loading dominate. The second set of data is hypothetical with resistance uncertainties as the major contribution to failure; whereas in the third set, loading and resistance have about equal contributions of uncertainties. The relative errors of computed risks with respect to Monte Carlo simulation results are compared. The results show that for conditions similar to those tested, most of the methods are computationally simpler than the Monte Carlo simulation, and can be used for risk calculation. Cautions to some of the methods are remarked.     

A patient-specific Monte Carlo dose-calculation method for photon beams

A patient-specific, CT-based, Monte Carlo dose-calculation method for photon beams has been developed to correctly account for inhomogeneity in the patient. The method employs the EGS4 system to sample the interaction of radiation in the medium. CT images are used to describe the patient geometry and to determine the density and atomic number in each voxel. The user code (MCPAT) provides the data describing the incident beams, and performs geometry checking and energy scoring in patient CT images. Several variance reduction techniques have been implemented to improve the computation efficiency. The method was verified with measured data and other calculations, both in homogeneous and inhomogeneous media. The method was also applied to a lung treatment, where significant differences in dose distributions, especially in the low-density region, were observed when compared with the results using an equivalent pathlength method. Comparison of the DVHs showed that the Monte Carlo calculated plan predicted an underdose of nearly 20% to the target, while the maximum doses to the cord and the heart were increased by 25% and 33%, respectively. These results suggested that the Monte Carlo method may have an impact on treatment designs, and also that it can be used as a benchmark to assess the accuracy of other dose calculation algorithms. The computation time for the lung case employing five 15-MV wedged beams, with an approximate field size of 13 X 13 cm and the dose grid size of 0.375 cm, was less than 14 h on a 175-MHz computer with a standard deviation of 1.5% in the high-dose region.     

A test of the "epinephrine hypothesis" in humans

The absorbed gamma dose rate in air 1 m above soil due to natural gamma emitters and 137Cs from the Chernobyl accident was determined inside a Quercus conferta Kit ecosystem in Northern Greece by combination of Monte Carlo simulations with the MCNP code and in-situ gamma spectrometry measurements. The total absorbed gamma dose rate in air is about 64 nGy h(-1), where 40% of this value is due to 137Cs and 60% to natural gamma emitters. The Monte Carlo simulations indicated that the gamma absorbed dose rate in air due to 137Cs is mainly due (70%) to unscattered radiation and to a lesser extent (30%) to the scattered radiation. The results obtained with the Monte Carlo simulations for the unscattered radiation were in very good agreement with the experimental values deduced by in-situ gamma spectrometry measurements. From the combination of the Monte Carlo simulations and in-situ gamma spectrometry measurements a conversion factor C = 1 nGy h(-1)/kBq m(-2) was deduced for 137Cs. This factor must be used with caution and only for forest sites similar to the one used for this work.     

备件寿命的计算机随机模拟

运用蒙特卡罗方法，在计算机上对备件寿命进行模拟仿真，从而为优化备件的储备提供了一套科学的、有效的方法，并对最终的计算精度进行了分析。     

Monte carlo simulation of clustering of alumina particles in turbulent liquid aluminum

A Monte Carlo method was developed to simulate the formation of clusters of alumina particles suspended in a turbulent pure liquid aluminum melt. With this approach, the chaotic movements of small alumina particles suspended within eddies smaller than the Kolmogoroff microscale were treated in a similar way to Brownian motion, and clusters were assumed to form once these particles collided with each other. The results obtained from the simulation indicate that clusters form very quickly during vigorous stirring and that the formation kinetics at the very beginning of mixing follow a second-order behavior. Clustering has been observed previously in the SiC-Al system and was also observed in the Al₂O₃-Al system in the present work.     

Testing for robustness in Monte Carlo studies.

Monte Carlo studies provide the information needed to help researchers select appropriate analytical procedures under design conditions in which the underlying assumptions of the procedures are not met. In Monte Carlo studies, the 2 errors that one could commit involve (a) concluding that a statistical procedure is robust when it is not or (b) concluding that it is not robust when it is. In previous attempts to apply standard statistical design principles to Monte Carlo studies, the less severe of these errors has been wrongly designated the Type I error. In this article, a method is presented for controlling the appropriate Type I error rate; the determination of the number of iterations required in a Monte Carlo study to achieve desired power is described; and a confidence interval for a test's true Type I error rate is derived. A robustness criterion is also proposed that is a compromise between W. G. Cochran's (1952) and J. V. Bradley's (1978) criteria. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of Random Material Properties on Buckling of Composite Plates

Composites exhibit a considerable amount of variation in their material properties because their fabrication∕manufacturing process involves a large number of parameters that cannot be controlled effectively. In the present study, the material properties have been modeled as random variables for better prediction of the system behavior. The classical laminate theory and first-order and higher-order shear deformation theories have been employed in deriving the governing equations for buckling of laminated rectangular plates. A mean-centered first-order perturbation technique has been used to find the second-order statistics of the buckling load. The approach has been validated by comparison with results of Monte Carlo simulation. Typical results have been presented for a plate with all edges simply supported. The effectiveness of the theories in predicting the buckling load dispersions has been examined. The sensitivity of buckling loads to change in the standard deviation of random material properties and to system parameters—side-to-thickness ratio and aspect ratio—has been examined for cross-ply symmetric and antisymmetric laminates.     

基于蒙特卡洛随机模拟法的矿业投资风险分析研究

蒙特卡洛随机模拟法是矿业工程投资经济评价风险分析中的一种重要方法。文章基于蒙特卡洛随机模拟法的数学思想，根据对模拟的统计学处理给出了相应的效果评判办法。同时以实例介绍了此方法在矿业投资的具体应用，并取得了较好的效果。     

Bearing Capacity of Rough Rigid Strip Footing on Cohesive Soil: Probabilistic Study

A probabilistic study on the bearing capacity of a rough rigid strip footing on a weightless cohesive soil is carried out to assess the influence of randomly distributed undrained shear strength. Nonlinear finite element analysis is merged with random field theory in conjunction with a Monte Carlo method. In a parametric study, the mean shear strength is held constant while the coefficient of variation and spatial correlation length of cohesion are varied systematically. The influence of the spatial variation of cohesion on the mean bearing capacity is discussed. The results are also presented in a probabilistic context to determine the probability of failure. A comparison between rough and smooth footing conditions is also made.     

A Monte Carlo study of the quality dependence of diamond thermoluminescent dosimeters in radiotherapy beams

Monte Carlo simulations with the EGS4 code system have been performed to determine the quality dependence of diamond TLDs in photon beams ranging from 25 kV to 25 MV x-rays and also in megavoltage electron beams. It has been shown that diamond TLDs in the form of discs of thickness 0.3 mm and diameter 5.64 mm show no significant dependence on the incident energy in clinical electron beams when irradiated close to dmax, but require an energy correction factor of 1.050 +/- 0.008 compared with diamond TLDs irradiated in 60Co gamma-rays. The correction factor increases with depth of irradiation and this effect is greater for thicker detectors. The Monte Carlo predicted sensitivity in x-ray beams is constant within 2.5% over the energy range 250 kV to 25 MV. However the sensitivity decreases by about 60% for 25 kV x-rays compared with 60Co gamma-rays.     

Experimental and Monte Carlo dosimetry of the Henschke applicator for high dose-rate 192Ir remote afterloading

We have performed extensive computational and experimental dosimetry of the Henschke applicator with respect to high dose-rate 192Ir brachytherapy using a GAMMAMED remote afterloader. Our goal was to generate clinically useful two- and three-dimensional look-up tables. Dose measurements of the Henschke applicator involved using TLD chips placed in a polystyrene phantom. Monte Carlo simulations were performed using the MCNP code. The computational models included the detailed geometry of 192Ir source, tandem tube, and shielded ovoid. The measured dose rates were corrected for the dependence of TLD sensitivity on the distance of measurement points from the source. Transit dose delivered during source extension to and retraction from a given dwell position was estimated by Monte Carlo simulations, and a correction was applied to the experimental values. For the applicator tandem, the ratio of dose rates obtained by MCNP to those measured by TLD chips ranges from 0.92 to 1.10 with an average of 0.98 and a standard deviation of 0.02. The measured and calculated dose rates at 1 cm on the transverse axis are 1.10 cGy U-1 h-1. For the shielded ovoid, the ratio ranges from 0.88 to 1.16 with an average of 1.00 and a standard deviation of 0.07. Causes of the discrepancy between the Monte Carlo and TLD results were identified. We found that the combined uncertainty of measured dose rates due to these causes is 5.6% for the applicator tandem and 8.4% for the shielded ovoid. Therefore, the results of the Monte Carlo simulation are considered to have been validated by the measurements within the uncertainty involved in the calculation and measurements.     

基于VB的晶粒长大的蒙特卡罗模拟

介绍正常晶粒长大的一般规律及其常用方法——蒙特卡罗方法．并采用VB语言编写了模拟正常晶粒长大的仿真系统．最后通过一算例获取了晶粒长大演变及晶粒尺寸随时问变化的关系．该算例说明了蒙特卡罗方法在模拟晶粒长大方面的直观性和有效性。     

Numerical Efficiency in Monte Carlo Simulations—Case Study of a River Thermodynamic Model

Trade-offs between precision of numerical solutions to deterministic models of the environment, and the number of model realizations achievable within a framework of Monte Carlo simulation, are investigated and discussed. A case study of a model of river thermodynamics is employed. It is shown that the tractability of Monte Carlo simulation relies on adaptation of the numerical solution time-step, giving results with a guaranteed error in the time domain as well as near-optimum speed of calibration under any chosen accuracy criteria. Time-step control is implemented using two adaptive Runge–Kutta methods: a second order scheme with first order error estimator, and an embedded fourth-fifth order scheme. In the case study, where the effects of sparse and imprecise data dominate the overall modeling error, both the schemes appear adequate. However, the higher order scheme is concluded to be generally more reliable and efficient, and has wide potential to improve the value of applying the Monte Carlo method to environmental simulation. The problem of reconciling spatial error with the specified temporal error is discussed.