Monte Carlo Simulation of Fluids in Curved Three-dimensional Space

Abstract

This work describes the methods required to perform computer simulations of three-dimensional fluids confined to the surface of a four-dimensional hypersphere. The use of such non-Euclidian spaces, or spherical boundary conditions, is convenient in cases where spatial inhomogeneities occur over length-scales comparable to that of the entire system. The form of the pressure equation in curved space is discussed, and the results of Monte Carlo simulations of hard spheres confined to the surface of a hypersphere are presented. Comparison of the simulation results to the Carnahan-Starling equation of state in flat space provides a basis for determining when curvature effects can be neglected.     

Monte Carlo Simulation of Release of Vesicular Content in Neuroendocrine Cells

The release of transmitter from the vesicle, its diffusion through the fusion pore, and the cleft and its interaction with the carbon electrode were simulated using the Monte Carlo method. According to the simulation the transmitter release is largely determined by geometric factors – the ratio of the fusion pore cross-sectional and vesicular areas, if the diffusion constant is as in the aqueous solution – but the speed of transmitter dissociation from the gel matrix plays an important role during the rise phase of release. Transmitter is not depleted near the entrance to the fusion pore and there is no cleft-to-vesicle feedback, but the depletion becomes evident if the diffusion constant is reduced, especially if the pore is wide. In general, the time course of amperometric currents closely resembles the time course of the simulated transmitter concentration in the cleft and the time course of release. Surprisingly, even a tenfold change of the electrode efficiency has only a marginal effect on the amplitude or the time course of amperometric currents. Greater electrode efficiency however lowers the cleft concentration, but only if the cleft is narrow. As the cleft widens the current amplitudes diminish and rise times lengthen, but the decay times are less affected. Moreover, the amplitude dependence of the rise and decay times becomes steeper as the cleft widens and/or as the release kinetics slows. Finally, lower diffusion constant of transmitter in the narrow cleft does not further prolong the amperometric currents, whose slow time course reflects slow release kinetics.     

Diffusion Microscopist Simulator: A General Monte Carlo Simulation System for Diffusion Magnetic Resonance Imaging

This article describes the development and application of an integrated, generalized, and efficient Monte Carlo simulation system for diffusion magnetic resonance imaging (dMRI), named Diffusion Microscopist Simulator (DMS). DMS comprises a random walk Monte Carlo simulator and an MR image synthesizer. The former has the capacity to perform large-scale simulations of Brownian dynamics in the virtual environments of neural tissues at various levels of complexity, and the latter is flexible enough to synthesize dMRI datasets from a variety of simulated MRI pulse sequences. The aims of DMS are to give insights into the link between the fundamental diffusion process in biological tissues and the features observed in dMRI, as well as to provide appropriate ground-truth information for the development, optimization, and validation of dMRI acquisition schemes for different applications. The validity, efficiency, and potential applications of DMS are evaluated through four benchmark experiments, including the simulated dMRI of white matter fibers, the multiple scattering diffusion imaging, the biophysical modeling of polar cell membranes, and the high angular resolution diffusion imaging and fiber tractography of complex fiber configurations. We expect that this novel software tool would be substantially advantageous to clarify the interrelationship between dMRI and the microscopic characteristics of brain tissues, and to advance the biophysical modeling and the dMRI methodologies.     

Monte Carlo Simulation of Buffered Diffusion into and out of a Model Synapse

Buffered diffusion occurs when ligands enter or leave a restricted space, such as a chemical synapse, containing a high density of binding sites. This study used Monte Carlo simulations to determine the time and spatial dependences of buffered diffusion without a priori assumptions about kinetics. The synapse was modeled as a box with receptors on one inner face. The exterior was clamped to some ligand concentration and ligands diffused through two sides. Onset and recovery simulations were carried out and the effects of receptor density, ligand properties and synapse geometry were investigated. This study determined equilibration times for binding and the spatial gradient of unliganded receptors. Onset was characterized by a high spatial gradient; equilibration was limited by the time needed for sufficient ligands to enter the synapse. Recovery showed a low spatial gradient with receptor equilibration limited by ligand rebinding. Decreasing ligand association rate or increasing ligand diffusion coefficient reduced the role of buffered diffusion and decreased the spatial gradient. Simulations with irreversible ligands showed larger, persistent spatial gradients. These simulations identify characteristics that can be used to test whether a synaptic process is governed by buffered diffusion. They also indicate that fundamental differences in synapse function may occur with irreversible ligands.     

Monte Carlo Simulation of Polyampholyte Chains

Abstract

Polyampholyte copolymers containing both positive and negative monomers regularly dispersed along the chain were studied. The Monte Carlo method was used to simulate chains with charged monomers interacting by screened Coulomb potential. The neutral polyampholyte chains collapse due to the attractive electrostatic interactions. The nonneutral chains are in extended conformations due to the repulsive polyelectrolyte effects that dominate the attractive polyampholyte interactions. The results are in good agreement with experiment.     

Design Space Development for the Extraction Process of Danhong Injection Using a Monte Carlo Simulation Method

A design space approach was applied to optimize the extraction process of Danhong injection. Dry matter yield and the yields of five active ingredients were selected as process critical quality attributes (CQAs). Extraction number, extraction time, and the mass ratio of water and material (W/M ratio) were selected as critical process parameters (CPPs). Quadratic models between CPPs and CQAs were developed with determination coefficients higher than 0.94. Active ingredient yields and dry matter yield increased as the extraction number increased. Monte-Carlo simulation with models established using a stepwise regression method was applied to calculate the probability-based design space. Step length showed little effect on the calculation results. Higher simulation number led to results with lower dispersion. Data generated in a Monte Carlo simulation following a normal distribution led to a design space with a smaller size. An optimized calculation condition was obtained with 10000 simulation times, 0.01 calculation step length, a significance level value of 0.35 for adding or removing terms in a stepwise regression, and a normal distribution for data generation. The design space with a probability higher than 0.95 to attain the CQA criteria was calculated and verified successfully. Normal operating ranges of 8.2-10 g/g of W/M ratio, 1.25-1.63 h of extraction time, and two extractions were recommended. The optimized calculation conditions can conveniently be used in design space development for other pharmaceutical processes.     

Monte Carlo Estimation for Nonlinear Non-Gaussian State Space Models

We develop a proposal or importance density for state spacemodels with a nonlinear non-Gaussian observation vector y p(y¦)and an unobserved linear Gaussian signal vector p(). The proposaldensity is obtained from the Laplace approximation of the smoothingdensity p(¦y). We present efficient algorithms to calculatethe mode of p(¦y) and to sample from the proposal density.The samples can be used for importance sampling and Markov chainMonte Carlo methods. The new results allow the application ofthese methods to state space models where the observation densityp(y¦) is not log-concave. Additional results are presentedthat lead to computationally efficient implementations. We illustratethe methods for the stochastic volatility model with leverage.     

Modelling Gas Adsorption in Slit-Pores Using Monte Carlo Simulation

Abstract

We discuss the use of Monte Carlo simulation to model the equilibrium adsorption of gases in slit pores. Databases of adsorption isotherms have been calculated for nitrogen, carbon-monoxide, methane and carbon-dioxide for a range of pressures, pore widths and temperatures. We discuss the implications of these results for materials characterisation procedures based on gas adsorption data.     

Monte Carlo Simulation of Binary Gas Adsorption in Zeolite Cavities

Abstract

Grand canonical Monte Carlo simulations have been performed for binary adsorption of Lennard-Jones molecules with point multipole moments in zeolite cavities of type X. Fluid-solid electrostatic interactions were taken into account. Phase diagrams and total coverage were calculated for three binaries and compared with experimental measurements. MC simulations gave good agreement with experiment for two mixtures (C₂H₄-CO₂ and CO₂-CH₄) but there were discrepancies between simulation and experiment for the system i-C₄H₁₀-C₂H₄. The dependence of excess Gibbs free energy on the composition and pressure was studied. Negative deviations from ideality are due to energetic heterogeneity and size effects. Unlike liquid-vapor equilibrium, deviations from the Lorentz-Berthelot mixing rules for the adsorbates have little effect upon the phase behavior. Density distributions show that the components compete for the high energy sites inside the cavity; depending on its relative strength of adsorption, one component may be excluded from such positions (CH₄ in CO₂-CH₄), or the two species may share sites inside the cavity (C₂H₄-CO₂).     

Stillinger-Weber Type Potentials in Monte Carlo Simulation of Amorphous Silicon

The growth of amorphous silicon on a substrate of a two-layer slab of crystalline silicon with various surface indices is simulated with Stillinger-Weber type interatomic potentials. The growth is realized by means of a continuum Monte Carlo method and the radial distribution functions are evaluated for various cases.     

Monte Carlo Simulation of Myoglobin Primary to Helical Structure

Abstract

A Monte Carlo simulation is presented of the formation of the individual helices of myoglobin from their primary to their helical structures. A simplified model in which each amino acid residue is replaced by a single interaction center is used. The small helices formed are in good agreement with experiment, while the larger helices are moderately well reproduced.     

方差组分估计方法MIVQUE和REML的模拟比较

利用ＭｏｎｔｅＣａｒｌｏ方法,对４种数据结构进行了ＭＩＶＱＵＥ和ＲＥＭＬ两种方差组分估计方法的模拟比较。方差组分估计所用的模型为奶牛育种中常用的公畜模型,它包括场年季固定效应、公牛组固定效应和公牛随机效应。４种数据结构中最大的有１２８４７个观察值,场年季效应和公牛效应水平数分别为７７８和４７,它与北京市目前可利用的奶牛头胎产奶量记录资料相当。最小的数据结构只有２００个观察值,１４８个场年季和２０头公牛。比较指标为估计值的偏差和方差（理论的或根据１０００次重复模拟所得的经验值）。结果表明,对于较大样本的数据结构,两种方法差异很小,它们间的估计值的相关接近于１,偏差小于真值的１％,方差近似相等。对于较小样本的数据结构,ＭＩＶＱＵＥ则明显优于ＲＥＭＬ。本研究还表明,对于ＲＥＭＬ来说,类似数据结构１的样本已能满足其渐近无偏性和有效性的大样本特性。     

Monte Carlo Simulation of Hydration of the Nucleic Acid Fragments

Abstract

Systems containing a base or a base pair and 25 water molecules, as well as a helical stack and 30 water molecules per base pair, have been simulated. Changes in the base hydration shell structure, after the bases have been included into the pair and then into the base pair stack are discussed. Hydration shells of several configurations of the base pair stacks are discussed. Probabilities of formation of the hydrogen-bonded bridges of 1, 2 and 3 water molecules between hydrophilic centres have been estimated. The hydration shell structure was shown to depend on the nature of the base pair and on the stack configuration, while dependence of the global hydration shell characteristics on the stack configuration has been proved to be rather slight. The most typical structural elements of hydration shells, in the glycosidic (minor in B-like conformation) and non-glycosidic (major) grooves, for different configurations of AU and GC stacks, have been found and discussed. The number of hydrogen bonds between water molecules and bases per water molecule was shown to change upon transformation of the stack from A to B configuration. This result is discussed in connection with the reasons for B to A conformational transition and the concept of “water economy”. Hydration shell patterns of NH₂-groups of AU and GC helical stacks differ significantly.     

Monte Carlo Simulation of Nonionic Surfactants at the Oil-Water Interface

Abstract

A Monte Carlo simulation method has been developed for modelling amphiphiles at an oil-water interface. Properties are calculated for the mixture water, benzene and tetraoxyethylene glycol dodecyl ether.     

基于时域的时间分辨荧光光谱的蒙特卡洛模拟

利用蒙特卡洛方法构建了生物组织基于时域的时间分辨荧光光谱的仿真模型,并将应用该模型获得的模拟结果与生物组织的实验光谱进行了比较。结果表明：吸收系数与散射系数分别影响光谱的不同区域;低浓度情况下,模拟结果与实验光谱符合得较好（x^2〈1．2）;高浓度下,实验光谱强度会被浓度效应削弱,以致影响其与模拟光谱的吻合程度。该方法为研究生物组织荧光光谱提供了一种新思路。     

Computer Simulation of Two-Dimensional Continuum Flows by the Direct Simulation Monte Carlo Method

Abstract

Computer simulations using particles are an attractive method to extract microscopic information of flow phenomena [1]. The molecular dynamics (MD) method, in which Newton's equations of motions are integrated, gives the temporal development of the system. In the MD simulation of fluid flows, the computational region is limited to atomistic scales [2]. On the other hand, the direct simulation Monte Carlo (DSMC) method, in which collisions of particles are made on a probabilistic basis, has a potential of treating a realistic system with a macroscopic scale length retaining the atomistic details. The DSMC method provides an efficient way to integrate the Boltzmann equation from the rarefied gas to the near-continuum region. Bird clarified the validity of the DSMC method in the near-continuum flow region [3]. However, the DSMC method has not been applied to the continuum region and compared with the continuum hydrodynamics.     

Model Testing in Radioligand/Receptor Interaction by Monte Carlo Simulation

Abstract

Monte Carlo simulations have been applied for evaluating the reliability of parameter estimates as well as for testing models in radioligand saturation binding experiments. Scatchard analysis was compared to the nonlinear least-square curve fitting method for one-site saturation binding curves. It was found that linear regression analysis from the transformed data in the Scatchard plot yielded generally less accurate parameter estimates than nonlinear regression analysis of untransformed data. The advantage of the nonlinear least-squares curve fitting method was especially pronounced in cases where the scatter and number of data points, as well as the radioligand concentration range, were chosen similar to less optimal experimental conditions. Under such circumstances, several K_D and B_max values derived by Scatchard analysis led to physically impossible negative values whereas the same data analyzed by nonlinear regression yielded reasonable parameter estimates. Furthermore, it was found that for both means of analysis, K_D and B_max correlated positively. In another set of Monte Carlo experiments, saturation binding curves involving two receptor sites were generated and subsequently analyzed according to both a one-site and a two-site model. The confidence with which one is able to distinguish the two-site model from nonlinear least-squares curve fitting was then estimated for optimal, as well as for, less ideal experimental condigions.     

Grand Canonical Monte Carlo Simulation for Solubility Calculation in Supercritical Extraction

Abstract

The Grand Canonical Ensemble Monte Carlo (GCEMC) technique is used to simulate highly nonideal dilute mixtures in the near vapor-liquid critical region. These systems are commonly found in supercritical fluid extraction processes. Mixtures composed of model CO₂/naphthalene/water molecules are studied. Very large and highly correlated concentration fluctuations were observed. It was found that when the total number of molecules in the system exceeded about 150, system size dependence was not significant. The GCEMC method breaks down when the system density exceeds about 1.5 times the solvent critical density due primarily to the low probability of successful addition and removal of the large naphthalene molecules. In some systems, the presence of a small amount of water caused a dramatic increase in the system density and in naphthalene solubility. By examining the radial distribution functions in these mixtures, the origin of this effect can be attributed to the preferential aggragation of the solute naphthalene molecules around the highly polar water molecules.     

Analysis of Light Transport Features in Stone Fruits Using Monte Carlo Simulation

The propagation of light in stone fruit tissue was modeled using the Monte Carlo (MC) method. Peaches were used as the representative model of stone fruits. The effects of the fruit core and the skin on light transport features in the peaches were assessed. It is suggested that the skin, flesh and core should be separately considered with different parameters to accurately simulate light propagation in intact stone fruit. The detection efficiency was evaluated by the percentage of effective photons and the detection sensitivity of the flesh tissue. The fruit skin decreases the detection efficiency, especially in the region close to the incident point. The choices of the source-detector distance, detection angle and source intensity were discussed. Accurate MC simulations may result in better insight into light propagation in stone fruit and aid in achieving the optimal fruit quality inspection without extensive experimental measurements.     

Grand Canonical Ensemble Monte Carlo Simulation on a Transputer Array

Five methods are described for the distribution over a 3D Transputer array of the calculation of the pair interaction component of particle energy. The most efficient method, expressed in terms of the time to complete a simulation, depends on the size of the simulation and the Transputer array. This dependence is quantified, with emphasis on Grand Canonical Ensemble Monte Carlo simulation, and yields criteria for the optimum strategy for parallel implementation of GCEMC algorithms. The equations derived are generally applicable, and have implications for the programming of Molecular Dynamics simulations.