The Underwater Communication Link(UCL)is a crucial component of Underwater Wireless Optical Communication(UWOC)systems,requiring optimised design to mitigate the high power attenuation inherent in seawater.To ensure t...The Underwater Communication Link(UCL)is a crucial component of Underwater Wireless Optical Communication(UWOC)systems,requiring optimised design to mitigate the high power attenuation inherent in seawater.To ensure the reliability of an optimal UCL design,it is essential to account for the three primary scattering regimes:forward scattering(FSC),backward scattering(BSC),and isotropic scattering(ISC)in seawater channels.This study introduces a new photon-tracking model based on a discrete equation,facilitating Monte Carlo Simulation(MCS)to evaluate how different scattering regimes influence received photon distribution.Three distinct Scattering Regime Contribution Weight(SRCW)probability sets were employed,each representing different UCL operational configurations dominated by specific scattering regimes.The proposed modeling approach enables a comprehensive assessment of the temporal characteristics of received optical pulses,channel loss,and time spread-ultimately defining the optimal UCL design parameters.The key findings of this study include:(1)Enhancing the FSC regime dominance leads to a quasi-light waveguide effect over link spans and small Fields of View(FOV)<25°,significantly improving channel performance in Harbor seawater compared to Coastal seawater.(2)A well-designed UCL with a small FOV(<25°)can minimise channel loss and time spread,ensuring high capacity and efficient performance in both Coastal and Harbor seawaters.(3)When BSC and ISC contributions exceed FSC dominance,the received optical pulse undergoes significant temporal broadening,particularly for larger FOV angles(>25°)and extended link spans.(4)The developed novel MCS-based discrete equation provides a simple yet robust model for simulating photon propagation in both homogeneous and inhomogeneous underwater channels.These insights contribute to developing more efficient and reliable UCL designs with military standards by enhancing UWOC system performance over a longer linkspan for a given limited optical power across various underwater environments.展开更多
Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of s...Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of spatial distribution of shallow gassy soils is indispensable prior to construction of underground projects in the area. Due to the costly conditions required in the site investigation for gassy soils, only a limited number of gas pressure data can be obtained in engineering practice, which leads to the uncertainty in characterizing spatial distribution of gassy soils. Determining the number of boreholes for investigating gassy soils and their corresponding locations is pivotal to reducing construction risk induced by gassy soils. However, this primarily relies on the engineering experience in the current site investigation practice. This study develops a probabilistic site investigation optimization method for planning investigation schemes (including the number and locations of boreholes) of gassy soils based on the conditional random field and Monte Carlo simulation. The proposed method aims to provide an optimal investigation scheme before the site investigation based on prior knowledge. Finally, the proposed approach is illustrated using a case study.展开更多
Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmenta...Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.展开更多
This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenari...This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenarios involving Normal,Platykurtic and Skewed distributions over different sample sizes and standard deviation values.In the study,standard deviation ratios were set as 2,3,4,1/2,1/3 and 1/4 and power comparisons were made between small and large sample sizes.For equal sample sizes,small sample sizes of 5,8,10,12,16 and 20 and large sample sizes of 25,50,75 and 100 were used.For different sample sizes,the combinations of(4,16),(8,16),(10,20),(16,4),(16,8)and(20,10)small sample sizes and(10,30),(30,10),(50,75),(50,100),(75,50),(75,100),(100,50)and(100,75)large sample sizes were examined in detail.According to the findings,the power analysis under variance heterogeneity conditions shows that the Siegel-Tukey test has a higher statistical power than the other nonparametric Savage test at small and large sample sizes.In particular,the Siegel-Tukey test was reported to offer higher precision and power under variance heterogeneity,regardless of having equal or different sample sizes.展开更多
Flat-panel X-ray sources(FPXSs)have many advantages in terms of compactness and low-dose imaging,enhancing their capability for novel X-ray applications.Experimental analysis of the X-ray characteristics and optimizin...Flat-panel X-ray sources(FPXSs)have many advantages in terms of compactness and low-dose imaging,enhancing their capability for novel X-ray applications.Experimental analysis of the X-ray characteristics and optimizing the anode panel of an FPXS are time-consuming,expensive,and sometimes impractical.In this study,a FPXS was prepared using a ZnO nanowire cold cathode and a molybdenum film anode target.Monte Carlo(MC)simulations were utilized to optimize the anode panel and obtain the average fluence,average energy,and spatial distribution of the X-rays for the ZnO nanowire FPXS.The accuracy of the MC simulations was verified by comparing the measured and simulated energy spectra.Optimization of the anode target considers the material,thickness,and morphology,whereas optimization of the substrate focuses on the material and thickness.The results show that the difference between the positions of the K-shell peaks in the measured and simulated energy spectra is within 0.26 keV.At the acceleration voltages of 30 kV,60 kV,and 90 kV,the optimal thicknesses of the tungsten array anode were 0.65μm,2.45μm,and 5μm,respectively,while the molybdenum array anode has the optimal thicknesses of 1.45μm,5.25μm,and 24μm,respectively.The microsemi-ellipsoidal anode with a recessed design showed a 5%increase in the transmitted X-ray fluence compared with the film target.The sapphire substrate with a thickness of 0.78 mm exhibits a mechanical strength comparable to that of a glass substrate with a thickness of 3 mm,implying that the former can increase the average X-ray fluence by reducing the filtration of X-rays.The findings of this study provide valuable guidance for the fabrication and optimization of the ZnO nanowire FPXS.展开更多
This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed ...This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.展开更多
Monte Carlo simulation techniques have become the quintessence and a pivotal nexus of inquiry in the realm of simulating photon movement within biological fabrics.Through the stochastic sampling of tissue archetypes d...Monte Carlo simulation techniques have become the quintessence and a pivotal nexus of inquiry in the realm of simulating photon movement within biological fabrics.Through the stochastic sampling of tissue archetypes delineated by explicit optical characteristics,Monte Carlo simulations possess the theoretical capacity to render unparalleled accuracy in the depiction of exceedingly intricate phenomena.Nonetheless,the quintessential challenge associated with Monte Carlo simulation methodologies resides in their extended computational duration,which significantly impedes the refinement of their precision.Consequently,this discourse is specifically dedicated to exploring innovations in strategies and technologies aimed at expediting Monte Carlo simulations.It delves into the foundational concepts of various acceleration tactics,evaluates these strategies concerning their speed,accuracy,and practicality,and amalgamates a comprehensive overview and critique of acceleration methodologies for Monte Carlo simulations.Ultimately,the discourse envisages prospective trajectories for the employment of Monte Carlo techniques within the domain of tissue optics.展开更多
Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience witho...Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis.This paper presents a comprehensive investigation,based on Monte Carlo simulation,into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades.It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations.More than 6×10^(7) sets of the registrations were simulated,whereas more than IOO registrations with real data were used to verify the results of simulation.The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground,when there is only a box set of spherical targets available.As a result,the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy.The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2.Therefore,the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner,contradicting to the traditional thought. Besides,the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.展开更多
GPU-based Monte Carlo(MC)simulations are highly valued for their potential to improve both the computational efficiency and accuracy of radiotherapy.However,in proton therapy,these methods often simplify human tissues...GPU-based Monte Carlo(MC)simulations are highly valued for their potential to improve both the computational efficiency and accuracy of radiotherapy.However,in proton therapy,these methods often simplify human tissues as water for nuclear reactions,disregarding their true elemental composition and thereby potentially compromising calculation accuracy.Consequently,this study developed the program g MCAP(GPU-based proton MC Algorithm for Proton therapy),incorporating precise discrete interactions,and established a refined nuclear reaction model(REFINED)that considers the actual materials of the human body.Compared to the approximate water model(APPROX),the REFINED model demonstrated an improvement in calculation accuracy of 3%.In particular,in high-density tissue regions,the maximum dose deviation between the REFINED and APPROX models was up to 15%.In summary,the g MCAP program can efficiently simulate 1 million protons within 1 s while significantly enhancing dose calculation accuracy in high-density tissues,thus providing a more precise and efficient engine for proton radiotherapy dose calculations in clinical practice.展开更多
Monte Carlo(MC) simulations have been performed to refine the estimation of the correction-toscaling exponent ω in the 2D φ^(4)model,which belongs to one of the most fundamental universality classes.If corrections h...Monte Carlo(MC) simulations have been performed to refine the estimation of the correction-toscaling exponent ω in the 2D φ^(4)model,which belongs to one of the most fundamental universality classes.If corrections have the form ∝ L^(-ω),then we find ω=1.546(30) andω=1.509(14) as the best estimates.These are obtained from the finite-size scaling of the susceptibility data in the range of linear lattice sizes L ∈[128,2048] at the critical value of the Binder cumulant and from the scaling of the corresponding pseudocritical couplings within L∈[64,2048].These values agree with several other MC estimates at the assumption of the power-law corrections and are comparable with the known results of the ε-expansion.In addition,we have tested the consistency with the scaling corrections of the form ∝ L^(-4/3),∝L^(-4/3)In L and ∝L^(-4/3)/ln L,which might be expected from some considerations of the renormalization group and Coulomb gas model.The latter option is consistent with our MC data.Our MC results served as a basis for a critical reconsideration of some earlier theoretical conjectures and scaling assumptions.In particular,we have corrected and refined our previous analysis by grouping Feynman diagrams.The renewed analysis gives ω≈4-d-2η as some approximation for spatial dimensions d <4,or ω≈1.5 in two dimensions.展开更多
The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology...The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in MS-Excel.Focused on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning requirements.The chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an escalation.The SS approach showed exceptional efficacy in calculating odds of failure that are notably low.Within computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO models.The ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most promising.This study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation infrastructure.These findings contribute to the enhancement of safety and reliability in real-world situations.展开更多
The effect of spin-1 impurities doping on the magnetic properties of a spin-3/2 Ising nanotube is investigated using Monte Carlo simulations within the Blume-Emery-Griffiths model in the presence of an external magnet...The effect of spin-1 impurities doping on the magnetic properties of a spin-3/2 Ising nanotube is investigated using Monte Carlo simulations within the Blume-Emery-Griffiths model in the presence of an external magnetic field. The thermal behaviors of the order parameters and different macroscopic instabilities as well as the hysteretic behavior of the material are examined in great detail as a function of the dopant density. It is found that the impurities concentration affects all the system magnetic properties generating for some specific values, compensation points and multi-cycle hysteresis. Doping conditions where the saturation/remanent magnetization and coercive field of the investigated material can be modified for permanent or soft magnets synthesis purpose are discussed.展开更多
The elementary reactions of propylene polymerization catalyzed by conventional Ziegler-Natta catalysts was proposed according to the comprehensive view and without considering the effect of any impurity in the materia...The elementary reactions of propylene polymerization catalyzed by conventional Ziegler-Natta catalysts was proposed according to the comprehensive view and without considering the effect of any impurity in the material on propylene polymerization. The Monte Carlo simulation technique was employed to investigate the kinetics of propylene polymerization in order to determine the validity of the stationary state assumption and the effects of the polymerization temperature on the polymerization. The simulated total amount of active species, which only increases quickly at the beginning of the polymerization, indicates that the stationary state assumption in the studied system is valid. Moreover, significant effects of polymerization temperature on the polymerization conversion, and the molecular weight and its distribution were also analyzed. The simulated results show that the consumption rate of propylene increases with the increase of polymerization temperature; the maximum values of the number-average degree of polymerization are constant at different polymerization temperatures, however, the peak appears earlier with the higher temperature; as the polymerization temperature increases, the average molecular weight decreases and the molecular weight distribution changes greatly.展开更多
A method for designing an X-ray flatness filter for medical electron linac is developed. It is used in the optimization process in the electron beam radiation system. Monte Carlo simulation method is used and two exam...A method for designing an X-ray flatness filter for medical electron linac is developed. It is used in the optimization process in the electron beam radiation system. Monte Carlo simulation method is used and two examples of real radiation system optimization processes for China-made medical electron linac are provided： 15 MV X- ray system of BJ-20 linac, and 12 MeV electron system of BJ-14. Results are verified by using the traditional method.展开更多
The Monte Carlo simulators with the three valley model and the full band Monte Carlo model are used to explore electron transport in bulk wurtzite gallium nitride (GaN).Comparison of the results based on the two mode...The Monte Carlo simulators with the three valley model and the full band Monte Carlo model are used to explore electron transport in bulk wurtzite gallium nitride (GaN).Comparison of the results based on the two models is made.The results based on both models are basically the same at the lower field region,but exhibit some differences at the higher field region.The electron average energy exhibits obvious difference at the high field region between the two models.This difference further causes several other differences of GaN properties,such as the drift velocity versus field characteristics,the repopulation.Because of the complicated energy band structures at the high energy region for wurtzite GaN,the analytical band structures in the three valley model can not cover all properties of the band structures of wurtzite GaN,so the results based on the full band Monte Carlo model should be more exact.展开更多
基金The Deanship of Scientific Research(DSR)at King Abdulaziz University(KAU),Jeddah,Saudi Arabia,has funded this project under Grant No.(KEP-PhD:72-130-1443).
文摘The Underwater Communication Link(UCL)is a crucial component of Underwater Wireless Optical Communication(UWOC)systems,requiring optimised design to mitigate the high power attenuation inherent in seawater.To ensure the reliability of an optimal UCL design,it is essential to account for the three primary scattering regimes:forward scattering(FSC),backward scattering(BSC),and isotropic scattering(ISC)in seawater channels.This study introduces a new photon-tracking model based on a discrete equation,facilitating Monte Carlo Simulation(MCS)to evaluate how different scattering regimes influence received photon distribution.Three distinct Scattering Regime Contribution Weight(SRCW)probability sets were employed,each representing different UCL operational configurations dominated by specific scattering regimes.The proposed modeling approach enables a comprehensive assessment of the temporal characteristics of received optical pulses,channel loss,and time spread-ultimately defining the optimal UCL design parameters.The key findings of this study include:(1)Enhancing the FSC regime dominance leads to a quasi-light waveguide effect over link spans and small Fields of View(FOV)<25°,significantly improving channel performance in Harbor seawater compared to Coastal seawater.(2)A well-designed UCL with a small FOV(<25°)can minimise channel loss and time spread,ensuring high capacity and efficient performance in both Coastal and Harbor seawaters.(3)When BSC and ISC contributions exceed FSC dominance,the received optical pulse undergoes significant temporal broadening,particularly for larger FOV angles(>25°)and extended link spans.(4)The developed novel MCS-based discrete equation provides a simple yet robust model for simulating photon propagation in both homogeneous and inhomogeneous underwater channels.These insights contribute to developing more efficient and reliable UCL designs with military standards by enhancing UWOC system performance over a longer linkspan for a given limited optical power across various underwater environments.
文摘Gassy soils are distributed in relatively shallow layers the Quaternary deposit in Hangzhou Bay area. The shallow gassy soils significantly affect the construction of underground projects. Proper characterization of spatial distribution of shallow gassy soils is indispensable prior to construction of underground projects in the area. Due to the costly conditions required in the site investigation for gassy soils, only a limited number of gas pressure data can be obtained in engineering practice, which leads to the uncertainty in characterizing spatial distribution of gassy soils. Determining the number of boreholes for investigating gassy soils and their corresponding locations is pivotal to reducing construction risk induced by gassy soils. However, this primarily relies on the engineering experience in the current site investigation practice. This study develops a probabilistic site investigation optimization method for planning investigation schemes (including the number and locations of boreholes) of gassy soils based on the conditional random field and Monte Carlo simulation. The proposed method aims to provide an optimal investigation scheme before the site investigation based on prior knowledge. Finally, the proposed approach is illustrated using a case study.
基金Postgraduate Innovation Top notch Talent Training Project of Hunan Province,Grant/Award Number:CX20220045Scientific Research Project of National University of Defense Technology,Grant/Award Number:22-ZZCX-07+2 种基金New Era Education Quality Project of Anhui Province,Grant/Award Number:2023cxcysj194National Natural Science Foundation of China,Grant/Award Numbers:62201597,62205372,1210456foundation of Hefei Comprehensive National Science Center,Grant/Award Number:KY23C502。
文摘Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.
文摘This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenarios involving Normal,Platykurtic and Skewed distributions over different sample sizes and standard deviation values.In the study,standard deviation ratios were set as 2,3,4,1/2,1/3 and 1/4 and power comparisons were made between small and large sample sizes.For equal sample sizes,small sample sizes of 5,8,10,12,16 and 20 and large sample sizes of 25,50,75 and 100 were used.For different sample sizes,the combinations of(4,16),(8,16),(10,20),(16,4),(16,8)and(20,10)small sample sizes and(10,30),(30,10),(50,75),(50,100),(75,50),(75,100),(100,50)and(100,75)large sample sizes were examined in detail.According to the findings,the power analysis under variance heterogeneity conditions shows that the Siegel-Tukey test has a higher statistical power than the other nonparametric Savage test at small and large sample sizes.In particular,the Siegel-Tukey test was reported to offer higher precision and power under variance heterogeneity,regardless of having equal or different sample sizes.
基金supported by the National Key Research and Development Program of China(Nos.2022YFA1204203 and 2022YFA1204201)Opening Fund of the State Key Laboratory of Optoelectronic Materials and Technologies at Sun Yat-sen University(No.OEMT-2023-KF-01)+1 种基金National Natural Science Foundation of China(Nos.61971463,82272131,and 82202960)the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515010537).
文摘Flat-panel X-ray sources(FPXSs)have many advantages in terms of compactness and low-dose imaging,enhancing their capability for novel X-ray applications.Experimental analysis of the X-ray characteristics and optimizing the anode panel of an FPXS are time-consuming,expensive,and sometimes impractical.In this study,a FPXS was prepared using a ZnO nanowire cold cathode and a molybdenum film anode target.Monte Carlo(MC)simulations were utilized to optimize the anode panel and obtain the average fluence,average energy,and spatial distribution of the X-rays for the ZnO nanowire FPXS.The accuracy of the MC simulations was verified by comparing the measured and simulated energy spectra.Optimization of the anode target considers the material,thickness,and morphology,whereas optimization of the substrate focuses on the material and thickness.The results show that the difference between the positions of the K-shell peaks in the measured and simulated energy spectra is within 0.26 keV.At the acceleration voltages of 30 kV,60 kV,and 90 kV,the optimal thicknesses of the tungsten array anode were 0.65μm,2.45μm,and 5μm,respectively,while the molybdenum array anode has the optimal thicknesses of 1.45μm,5.25μm,and 24μm,respectively.The microsemi-ellipsoidal anode with a recessed design showed a 5%increase in the transmitted X-ray fluence compared with the film target.The sapphire substrate with a thickness of 0.78 mm exhibits a mechanical strength comparable to that of a glass substrate with a thickness of 3 mm,implying that the former can increase the average X-ray fluence by reducing the filtration of X-rays.The findings of this study provide valuable guidance for the fabrication and optimization of the ZnO nanowire FPXS.
基金supported by Project of Chongqing Science and Technology Bureau (cstc2022jxjl0005)。
文摘This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.
基金funded by the Chinese Academy of Medical Science health innovation project(grant nos.2021-I2M-1-042,2021-I2M-1-058,and 2022-I2M-C&T-A-005)Tianjin Outstanding Youth Fund Project(grant no.20JCJQIC00230)CAMS Innovation Fund for Medical Sciences(CIFMS)(grant no.2022-I2M-C&T-B-012).
文摘Monte Carlo simulation techniques have become the quintessence and a pivotal nexus of inquiry in the realm of simulating photon movement within biological fabrics.Through the stochastic sampling of tissue archetypes delineated by explicit optical characteristics,Monte Carlo simulations possess the theoretical capacity to render unparalleled accuracy in the depiction of exceedingly intricate phenomena.Nonetheless,the quintessential challenge associated with Monte Carlo simulation methodologies resides in their extended computational duration,which significantly impedes the refinement of their precision.Consequently,this discourse is specifically dedicated to exploring innovations in strategies and technologies aimed at expediting Monte Carlo simulations.It delves into the foundational concepts of various acceleration tactics,evaluates these strategies concerning their speed,accuracy,and practicality,and amalgamates a comprehensive overview and critique of acceleration methodologies for Monte Carlo simulations.Ultimately,the discourse envisages prospective trajectories for the employment of Monte Carlo techniques within the domain of tissue optics.
基金Key Research and Development Program of Guangdong Province (No.2020B0101130009)
文摘Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis.This paper presents a comprehensive investigation,based on Monte Carlo simulation,into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades.It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations.More than 6×10^(7) sets of the registrations were simulated,whereas more than IOO registrations with real data were used to verify the results of simulation.The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground,when there is only a box set of spherical targets available.As a result,the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy.The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2.Therefore,the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner,contradicting to the traditional thought. Besides,the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.
文摘GPU-based Monte Carlo(MC)simulations are highly valued for their potential to improve both the computational efficiency and accuracy of radiotherapy.However,in proton therapy,these methods often simplify human tissues as water for nuclear reactions,disregarding their true elemental composition and thereby potentially compromising calculation accuracy.Consequently,this study developed the program g MCAP(GPU-based proton MC Algorithm for Proton therapy),incorporating precise discrete interactions,and established a refined nuclear reaction model(REFINED)that considers the actual materials of the human body.Compared to the approximate water model(APPROX),the REFINED model demonstrated an improvement in calculation accuracy of 3%.In particular,in high-density tissue regions,the maximum dose deviation between the REFINED and APPROX models was up to 15%.In summary,the g MCAP program can efficiently simulate 1 million protons within 1 s while significantly enhancing dose calculation accuracy in high-density tissues,thus providing a more precise and efficient engine for proton radiotherapy dose calculations in clinical practice.
文摘Monte Carlo(MC) simulations have been performed to refine the estimation of the correction-toscaling exponent ω in the 2D φ^(4)model,which belongs to one of the most fundamental universality classes.If corrections have the form ∝ L^(-ω),then we find ω=1.546(30) andω=1.509(14) as the best estimates.These are obtained from the finite-size scaling of the susceptibility data in the range of linear lattice sizes L ∈[128,2048] at the critical value of the Binder cumulant and from the scaling of the corresponding pseudocritical couplings within L∈[64,2048].These values agree with several other MC estimates at the assumption of the power-law corrections and are comparable with the known results of the ε-expansion.In addition,we have tested the consistency with the scaling corrections of the form ∝ L^(-4/3),∝L^(-4/3)In L and ∝L^(-4/3)/ln L,which might be expected from some considerations of the renormalization group and Coulomb gas model.The latter option is consistent with our MC data.Our MC results served as a basis for a critical reconsideration of some earlier theoretical conjectures and scaling assumptions.In particular,we have corrected and refined our previous analysis by grouping Feynman diagrams.The renewed analysis gives ω≈4-d-2η as some approximation for spatial dimensions d <4,or ω≈1.5 in two dimensions.
文摘The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in MS-Excel.Focused on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning requirements.The chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an escalation.The SS approach showed exceptional efficacy in calculating odds of failure that are notably low.Within computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO models.The ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most promising.This study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation infrastructure.These findings contribute to the enhancement of safety and reliability in real-world situations.
文摘The effect of spin-1 impurities doping on the magnetic properties of a spin-3/2 Ising nanotube is investigated using Monte Carlo simulations within the Blume-Emery-Griffiths model in the presence of an external magnetic field. The thermal behaviors of the order parameters and different macroscopic instabilities as well as the hysteretic behavior of the material are examined in great detail as a function of the dopant density. It is found that the impurities concentration affects all the system magnetic properties generating for some specific values, compensation points and multi-cycle hysteresis. Doping conditions where the saturation/remanent magnetization and coercive field of the investigated material can be modified for permanent or soft magnets synthesis purpose are discussed.
基金The National Natural Science Foundation of China(No.20406016)the Project of Fujian Petrochemical Company of SIN-OPEC (No.MS/FJ-08-JS-15-2005-01).
文摘The elementary reactions of propylene polymerization catalyzed by conventional Ziegler-Natta catalysts was proposed according to the comprehensive view and without considering the effect of any impurity in the material on propylene polymerization. The Monte Carlo simulation technique was employed to investigate the kinetics of propylene polymerization in order to determine the validity of the stationary state assumption and the effects of the polymerization temperature on the polymerization. The simulated total amount of active species, which only increases quickly at the beginning of the polymerization, indicates that the stationary state assumption in the studied system is valid. Moreover, significant effects of polymerization temperature on the polymerization conversion, and the molecular weight and its distribution were also analyzed. The simulated results show that the consumption rate of propylene increases with the increase of polymerization temperature; the maximum values of the number-average degree of polymerization are constant at different polymerization temperatures, however, the peak appears earlier with the higher temperature; as the polymerization temperature increases, the average molecular weight decreases and the molecular weight distribution changes greatly.
基金Supported by the National Natural Science Foundation of China (60672104,10675013)the Na-tional Basic Research Program of China ("973"Program)(2006CB705705)+1 种基金the 10th Five-Year Plan of the Ministry of Science and Technology of China(2001BA706B-05)the Joint Research Foundation of Beijing Municipal Commissionof Education~~
文摘A method for designing an X-ray flatness filter for medical electron linac is developed. It is used in the optimization process in the electron beam radiation system. Monte Carlo simulation method is used and two examples of real radiation system optimization processes for China-made medical electron linac are provided： 15 MV X- ray system of BJ-20 linac, and 12 MeV electron system of BJ-14. Results are verified by using the traditional method.
文摘The Monte Carlo simulators with the three valley model and the full band Monte Carlo model are used to explore electron transport in bulk wurtzite gallium nitride (GaN).Comparison of the results based on the two models is made.The results based on both models are basically the same at the lower field region,but exhibit some differences at the higher field region.The electron average energy exhibits obvious difference at the high field region between the two models.This difference further causes several other differences of GaN properties,such as the drift velocity versus field characteristics,the repopulation.Because of the complicated energy band structures at the high energy region for wurtzite GaN,the analytical band structures in the three valley model can not cover all properties of the band structures of wurtzite GaN,so the results based on the full band Monte Carlo model should be more exact.
