Evaluation of the population distribution of dietary contaminant exposure in an Arctic population using Monte Carlo statistics.

This paper examines the asymptotic null distributions of the J and Cox non-nested tests in the framework of two linear regression models with nearly orthogonal non-nested regressors. The analysis is based on the concept of near population orthogonality (NPO), according to which the non-nested regressors in the two models are nearly uncorrelated in the population distribution from which they are drawn. New distributional results emerge under NPO. The J and Cox tests tend to two different random variables asymptotically, each of which is expressible as a function of a nuisance parameter, c, a N(0,1) variate and a χ2(q) variate, where q is the number of non-nested regressors in the alternative model. The Monte Carlo method is used to show the relevance of the new results in finite samples and to compute alternative critical values for the two tests under NPO by plugging consistent estimates of c into the relevant asymptotic expressions. An empirical example illustrates the ‘plug in’ procedure.

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Integrating physiologically based kinetic (PBK) and Monte Carlo modelling to predict inter-individual and inter-ethnic variation in bioactivation and liver toxicity of lasiocarpine

Archives of Toxicology ◽

10.1007/s00204-019-02563-x ◽

2019 ◽

Vol 93 (10) ◽

pp. 2943-2960 ◽

Cited By ~ 1

Author(s):

Jia Ning ◽

Ivonne M. C. M. Rietjens ◽

Marije Strikwold

Keyword(s):

Monte Carlo ◽

Liver Toxicity ◽

Population Distribution ◽

Geometric Mean ◽

Caucasian Population ◽

Individual Variations ◽

Physiologically Based ◽

Adjustment Factors ◽

Human Kinetic

Abstract The aim of the present study was to predict the effect of inter-individual and inter-ethnic human kinetic variation on the sensitivity towards acute liver toxicity of lasiocarpine in the Chinese and the Caucasian population, and to derive chemical specific adjustment factors (CSAFs) by integrating variation in the in vitro kinetic constants Vmax and Km, physiologically based kinetic (PBK) modelling and Monte Carlo simulation. CSAFs were derived covering the 90th and 99th percentile of the population distribution of pyrrole glutathione adduct (7-GS-DHP) formation, reflecting bioactivation. The results revealed that in the Chinese population, as compared to the Caucasian population, the predicted 7-GS-DHP formation at the geometric mean, the 90th and the 99th percentile were 2.1-, 3.3- and 4.3-fold lower respectively. The CSAFs obtained using the 99th percentile values were 8.3, 17.0 and 19.5 in the Chinese, the Caucasian population and the two populations combined, respectively, while the CSAFs were generally 3.0-fold lower at the 90th percentile. These results indicate that when considering the formation of 7-GS-DHP the Caucasian population may be more sensitive towards acute liver toxicity of lasiocarpine, and further point out that the default safety factor of 3.16 for inter-individual human kinetic differences may not be sufficiently protective. Altogether, the results obtained demonstrate that integrating PBK modelling with Monte Carlo simulations using human in vitro data is a powerful strategy to quantify inter-individual variations in kinetics, and can be used to refine the human risk assessment of pyrrolizidine alkaloids.

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Sampling Conformational Changes of Bound Ligands Using Nonequilibrium Candidate Monte Carlo

10.26434/chemrxiv.10003412.v1 ◽

2019 ◽

Author(s):

Sukanya Sasmal ◽

Samuel C. Gill ◽

Nathan M. Lim ◽

David Mobley

Keyword(s):

Monte Carlo ◽

Conformational Changes ◽

Population Distribution ◽

Computational Cost ◽

Binding Pocket ◽

Umbrella Sampling ◽

Binding Modes ◽

Flexible Part ◽

Acceptance Rates ◽

Flexible Ligands

Flexible ligands often have multiple binding modes or bound conformations that differ by rotation of a portion of the molecule around internal rotatable bonds. Knowledge of these binding modes is important for understanding the interactions stabilizing the ligand in the binding pocket, and also for calculating accurate binding affinities. In this work, we use a hybrid molecular dynamics (MD)/non-equilibrium candidate Monte Carlo (NCMC) method to sample the different binding modes of several flexible ligands and also to estimate the population distribution of the modes. The NCMC move proposal is divided into three parts. The flexible part of the ligand is alchemically turned off by decreasing the electrostatics and steric interactions gradually, followed by rotating the rotatable bond by a random angle and then slowly turning the ligand back on to its fully interacting state. The alchemical steps prior to and after the move proposal help the surrounding protein and water atoms in the binding pocket relax around the proposed ligand conformation and increase move acceptance rates. The protein-ligand system is propagated using classical MD in between the NCMC proposals. Using this MD/NCMC method, we were able to correctly reproduce the different binding modes of inhibitors binding to two kinase targets -- c-Jun N-terminal kinase-1 and cyclin-dependent kinase 2 -- at a much lower computational cost compared to conventional MD and umbrella sampling. This method is available as a part of the BLUES software package.

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Sampling Conformational Changes of Bound Ligands Using Nonequilibrium Candidate Monte Carlo

10.26434/chemrxiv.10003412 ◽

2019 ◽

Author(s):

Sukanya Sasmal ◽

Samuel C. Gill ◽

Nathan M. Lim ◽

David Mobley

Keyword(s):

Monte Carlo ◽

Conformational Changes ◽

Population Distribution ◽

Computational Cost ◽

Binding Pocket ◽

Umbrella Sampling ◽

Binding Modes ◽

Flexible Part ◽

Acceptance Rates ◽

Flexible Ligands

Flexible ligands often have multiple binding modes or bound conformations that differ by rotation of a portion of the molecule around internal rotatable bonds. Knowledge of these binding modes is important for understanding the interactions stabilizing the ligand in the binding pocket, and also for calculating accurate binding affinities. In this work, we use a hybrid molecular dynamics (MD)/non-equilibrium candidate Monte Carlo (NCMC) method to sample the different binding modes of several flexible ligands and also to estimate the population distribution of the modes. The NCMC move proposal is divided into three parts. The flexible part of the ligand is alchemically turned off by decreasing the electrostatics and steric interactions gradually, followed by rotating the rotatable bond by a random angle and then slowly turning the ligand back on to its fully interacting state. The alchemical steps prior to and after the move proposal help the surrounding protein and water atoms in the binding pocket relax around the proposed ligand conformation and increase move acceptance rates. The protein-ligand system is propagated using classical MD in between the NCMC proposals. Using this MD/NCMC method, we were able to correctly reproduce the different binding modes of inhibitors binding to two kinase targets -- c-Jun N-terminal kinase-1 and cyclin-dependent kinase 2 -- at a much lower computational cost compared to conventional MD and umbrella sampling. This method is available as a part of the BLUES software package.

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Mitigating the zonal effect in modeling urban population density functions by Monte Carlo simulation

Environment and Planning B Urban Analytics and City Science ◽

10.1177/2399808317749832 ◽

2018 ◽

Vol 46 (6) ◽

pp. 1061-1078 ◽

Cited By ~ 1

Author(s):

Fahui Wang ◽

Cuiling Liu ◽

Yaping Xu

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Population Density ◽

Urban Population ◽

Distance Measure ◽

Population Distribution ◽

Empirical Studies ◽

Negative Exponential Function ◽

Negative Exponential ◽

Uniform Area

Most empirical studies indicate that the pattern of declining urban population density with distance from the city center is best captured by a negative exponential function. Such studies usually use aggregated data in census area units that are subject to several criticisms such as modifiable areal unit problem, unfair sampling, and uncertainty in distance measure. In order to mitigate these concerns associated, this paper uses Monte Carlo simulation to generate individual residents that are consistent with known patterns of population distribution. By doing so, we are able to aggregate population back to various uniform area units to examine the scale and zonal effects explicitly. The case study in Chicago area indicates that the best fitting density function remains exponential for data in census tracts or block groups, however, the logarithmic function becomes a better fit when uniform area units such as squares, triangles or hexagons are used. The study also suggests that the scale effect remain to some extent in all area units, and the zonal effect be largely mitigated by uniform area units of regular shape.

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The distributions of the J and Cox non-nested tests in regression models with weakly correlated regressors

10.32920/14640891.v1 ◽

2021 ◽

Author(s):

Leo Michelis

Keyword(s):

Monte Carlo ◽

Alternative Model ◽

Regression Models ◽

Population Distribution ◽

Nuisance Parameter ◽

Linear Regression Models ◽

Null Distributions ◽

Finite Samples ◽

The Monte Carlo Method ◽

Asymptotic Expressions

This paper examines the asymptotic null distributions of the J and Cox non-nested tests in the framework of two linear regression models with nearly orthogonal non-nested regressors. The analysis is based on the concept of near population orthogonality (NPO), according to which the non-nested regressors in the two models are nearly uncorrelated in the population distribution from which they are drawn. New distributional results emerge under NPO. The J and Cox tests tend to two different random variables asymptotically, each of which is expressible as a function of a nuisance parameter, c, a N(0,1) variate and a χ2(q) variate, where q is the number of non-nested regressors in the alternative model. The Monte Carlo method is used to show the relevance of the new results in finite samples and to compute alternative critical values for the two tests under NPO by plugging consistent estimates of c into the relevant asymptotic expressions. An empirical example illustrates the ‘plug in’ procedure.

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Outbursts of comet Schwassmann-Wachmann 1, and the cloud of interplanetary boulders

International Astronomical Union Colloquium ◽

10.1017/s0252921100034035 ◽

1974 ◽

Vol 22 ◽

pp. 307 ◽

Cited By ~ 3

Author(s):

Zdenek Sekanina

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Interplanetary Space ◽

Porous Matrix ◽

Maximum Diameter ◽

Expansion Velocity ◽

Solid Constituent ◽

Meteoric Material ◽

Periodic Comet

AbstractIt is suggested that the outbursts of Periodic Comet Schwassmann-Wachmann 1 are triggered by impacts of interplanetary boulders on the surface of the comet’s nucleus. The existence of a cloud of such boulders in interplanetary space was predicted by Harwit (1967). We have used the hypothesis to calculate the characteristics of the outbursts – such as their mean rate, optically important dimensions of ejected debris, expansion velocity of the ejecta, maximum diameter of the expanding cloud before it fades out, and the magnitude of the accompanying orbital impulse – and found them reasonably consistent with observations, if the solid constituent of the comet is assumed in the form of a porous matrix of lowstrength meteoric material. A Monte Carlo method was applied to simulate the distributions of impacts, their directions and impact velocities.

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Monte Carlo Algorithms for Moments of Transition Arrays

International Astronomical Union Colloquium ◽

10.1017/s0252921100107468 ◽

1988 ◽

Vol 102 ◽

pp. 79-81

Author(s):

A. Goldberg ◽

S.D. Bloom

Keyword(s):

Monte Carlo ◽

State Vector ◽

Basis Vector ◽

Collective State ◽

Dispersion Characteristics ◽

Dipole Strength ◽

The Third ◽

Monte Carlo Algorithms ◽

Third Moment ◽

Very High

AbstractClosed expressions for the first, second, and (in some cases) the third moment of atomic transition arrays now exist. Recently a method has been developed for getting to very high moments (up to the 12th and beyond) in cases where a “collective” state-vector (i.e. a state-vector containing the entire electric dipole strength) can be created from each eigenstate in the parent configuration. Both of these approaches give exact results. Herein we describe astatistical(or Monte Carlo) approach which requires onlyonerepresentative state-vector |RV> for the entire parent manifold to get estimates of transition moments of high order. The representation is achieved through the random amplitudes associated with each basis vector making up |RV>. This also gives rise to the dispersion characterizing the method, which has been applied to a system (in the M shell) with≈250,000 lines where we have calculated up to the 5th moment. It turns out that the dispersion in the moments decreases with the size of the manifold, making its application to very big systems statistically advantageous. A discussion of the method and these dispersion characteristics will be presented.

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Electron Scattering in Solids

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100133618 ◽

1990 ◽

Vol 48 (2) ◽

pp. 4-5

Author(s):

Ryuichi Shimizu ◽

Ze-Jun Ding

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Angular Distribution ◽

Elastic Scattering ◽

Electron Scattering ◽

Cross Sections ◽

Expansion Method ◽

Electron Excitation ◽

Partial Wave Expansion ◽

Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

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Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100134922 ◽

1990 ◽

Vol 48 (2) ◽

pp. 264-265

Author(s):

D. R. Liu ◽

S. S. Shinozaki ◽

R. J. Baird

Keyword(s):

Thin Film ◽

Thin Films ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Compound Semiconductors ◽

Energy Dispersive Analysis ◽

X Ray ◽

Metastable Alloys ◽

Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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