The mean straight length of a short polyelectrolyte: a Monte Carlo study

1992 ◽  
Vol 96 (13) ◽  
pp. 5553-5560 ◽  
Author(s):  
Chava Brender
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
The Mean

Monte Carlo study of the depth and lateral range of low-energy projectiles in solids

1980 ◽  
Vol 58 (12) ◽  
pp. 1738-1747 ◽  
Author(s):  
B. M. Latta
Keyword(s):  
Monte Carlo ◽  
Numerical Solutions ◽  
Monte Carlo Study ◽  
Equal Mass ◽  
Thomas Fermi ◽  
Hartree Fock ◽  
Fermi Interaction ◽  
The Mean ◽  
Lateral Range ◽  
Good Agreement

For heavy projectiles on light targets, the experimental measurements of mean-depth and of lateral-range straggle indicate discrepancies of up to 100% in the previous numerical solutions which are based upon a Thomas–Fermi interaction potential. In contrast, the present Monte Carlo (MC) results, which are based upon a solid-state Thomas–Fermi (SSTF) interaction, are in good agreement with experiment. The present SSTF mean-depth estimates are also in good agreement with estimates based on semiempirical potentials and with estimates based on Hartree–Fock–Slater interaction potentials. There remain small discrepancies between experiment and all theoretical estimates of the mean depth. In the case of the lateral-range straggle, the present MC SSTF results are in excellent agreement with experiment. The previous large discrepancies between theory and experiment are attributed, in part, to the choice of potential and, in part, to the numerical methods used to obtain the lateral-range straggle. In addition, the present MC SSTF calculations of the mean-depth and lateral-range straggle for equal mass and light projectile on heavy target collision pairs are in closer agreement with existing numerical estimates.

Comparison of Y-90 and Ho-166 Dosimetry Using Liver Phantom: A Monte Carlo Study

2021 ◽  
Vol 21 ◽  
Author(s):  
Ayşe Karadeniz Yıldırım ◽  
Handan Tanyıldızı Kökkülünk
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Liver Parenchyma ◽  
Total Activity ◽  
Good Alternative ◽  
Liver Malignancy ◽  
Liver Model ◽  
Absorbed Doses ◽  
The Mean ◽  
Liver Phantom

Background: It is estimated that more than 1 million people are diagnosed with liver malignancy each year and one of the treatments is radioembolization with Y-90 and Ho-166. Objective: The aim of this study is to calculate the absorbed doses caused by Y-90 and Ho-166 in tumor and liver parenchyma using a phantom via Monte Carlo method. Methods: A liver model phantom including a tumor imitation of sphere (r =1.5cm) was defined in GATE. The total activity of 40 mCi Y-90 and Ho-166 was prescribed into tumor imitation as source and 2x2x2 mm3 voxel-sized DoseActors were identified at 30 locations. The simulation, performed to calculate the absorbed doses left by particles during 1 second for Y-90 and Ho-166, was run for a total of 10 days and 11 days, respectively. Total doses were calculated by taking the doses occurring in 1 second as a reference. Results: The maximum absorbed doses were found to be 2.334E+03±1.576E+01 Gy for Y-90 and 7.006E+02±6.013E-01 Gy for Ho-166 at the center of tumor imitation. The minimum absorbed doses were found to be 2.133E-03±1.883E-01 Gy for Y-90 and 1.152E-02±1.036E-03 Gy for Ho-166 at the farthest location from source. The mean absorbed doses in tumor imitation were found to be 1.50E+03±1.36E+00 Gy and 4.58E+02±4.75E-01 Gy for Y-90 and Ho-166, respectively. And, the mean absorbed doses in normal parenchymal tissue were found to be2.07E+01±9.58E-02 Gy and 3.79E+00±2.63E-02 Gy for Y-90 and Ho-166, respectively. Conclusion: Based on the results, Ho-166 is a good alternative to Y-90 according to dosimetric evaluation.

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

Detecting Between-Groups Heteroscedasticity in MMR: A Monte Carlo Study

2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study
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