The recent development of on-the-fly atomistic kinetic Monte Carlo methods has led to an increased amount attention on the methods and their corresponding capabilities and applications. In this review, the framework and current status of Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) are discussed. SEAKMC particularly focuses on defect interaction and evolution with atomistic details without assuming potential defect migration/interaction mechanisms and energies. The strength and limitation of using an active volume, the key concept introduced in SEAKMC, are discussed. Potential criteria for characterizing an active volume are discussed and the influence of active volume size on saddle point energies is illustrated. A procedure starting with a small active volume followed by larger active volumes was found to possess higher efficiency. Applications of SEAKMC, ranging from point defect diffusion, to complex interstitial cluster evolution, to helium interaction with tungsten surfaces, are ...

Markov Chain Monte Carlo Method without Detailed Balance - Condensed Matter > Statistical Mechanics. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.

A Monte Carlo study of the transient response of single photon absorption in X-ray pixel detectors is presented. The simulation results have been combined with Monte Carlo simulation of the X-ray photon transport and absorption, and used to estimate the image properties of a detector system, including the pixel array and readout electronics. The study includes several different simulation challenges, such as full band Monte Carlo simulation of charge transport in large devices (300 mu m * 100 mu m), modelling of three-dimensional electrostatic effects using cylindrical coordinates, Monte Carlo simulation of photon transport and absorption, and a system level Monte Carlo simulation of the entire pixel detector and readout. ...

Markov Chain Monte Carlo simulation has received considerable attention within the past decade as reportedly one of the most powerful techniques for the first passage probability estimation of dynamic systems. A very popular method in this direction capable of estimating probability of rare events with low computation cost is the subset simulation (SS). The idea of the method is to break a rare event into a sequence of more probable events which are easy to be estimated based on the conditional simulation techniques. Recently, two algorithms have been proposed in order to increase the efficiency of the method by modifying the conditional sampler. In this paper, applicability of the original SS is compared to the recently introduced modifications of the method on a wind turbine model. The model incorporates a PID pitch controller which aims at keeping the rotational speed of the wind turbine rotor equal to its nominal value. Finally Monte Carlo simulations are performed which allow assessment of ...

Introduction Proton therapy is used to treat malignant tumors such as melanoma inside the eye. Proton particles are adjusted according to various parameters such as tumor size and position and patients distance from the proton source. The purpose of this study was to assess absorbed doses in eyes and various tumors found in the area of sclera and choroid and the adjacent tissues in radiotherapy while changing most important proton therapy parameters such as moderators thickness (1.5-1.9 cm), exposure radius (0.5-0.8 cm), and proton energy beam (53.5-65 MeV). Materials and Methods A proton therapy system of Laboratori Nazionali del Sud-INFNwas simulated by Monte Carlo method. Moreover, the eye and its components were simulated using concentric spheres. To obtain a more accurate results, real density of eye components such as cornea and lens, were applied for simulation. Then, the absorbed dose of eye and eye tumor, in choroid and sclera areas, were calculated by Monte Carlo method. Results The absorbed

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Target tracking is a challenging task and generally no analytical solution is available, especially for the multi-target tracking systems. To address this problem, probability hypothesis density (PHD) filter is used by propagating the PHD instead of the full multi-target posterior. Recently, the particle flow filter based on the log homotopy provides a new way for state estimation. In this paper, we propose a novel sequential Monte Carlo (SMC) implementation for the PHD filter assisted by the particle flow (PF), which is called PF-SMCPHD filter. Experimental results show that our proposed filter has higher accuracy than the SMC-PHD filter and is computationally cheaper than the Gaussian mixture PHD (GM-PHD) filter.. ...

It is a computation process that uses random numbers to produce an outcome(s). Instead of having fixed inputs, probability distributions are assigned to some or all of the inputs. This will generate a probability distribution for the output after the simulation is run.. For example, a Monte Carlo algorithm can be used to estimate the value of π. The amount of area within a quarter-circle of radius 1 depends on the value of π. The probability that a randomly-chosen point will lie in that quarter-circle depends on the area of the circle. If points are placed randomly in a square with sides of length 1, the percentage of points that fall within a quarter-circle of radius 1 will depend on the value of π. A Monte Carlo algorithm would randomly place points in the square and use the percentage of points falling inside of the circle to estimate the value of π.This is an effective way for making approximations.. In modern communication systems, the quality of information exchange is determined by ...

TY - JOUR. T1 - Adsorption equilibrium of polar/non-polar mixtures on MCM-41. T2 - Experiments and Monte Carlo simulation. AU - Yun., J. H.. AU - He, Y.. AU - Otero, M.. AU - Düren, T.. AU - Seaton, N. A.. PY - 2002/12/1. Y1 - 2002/12/1. N2 - We have studied the adsorption of mixtures of polar and non-polar gases in MCM-41. MCM-41 is a suitable model on which to test our understanding of adsorption at the molecular level, and to evaluate methods for the prediction of multicomponent adsorption equilibrium. The adsorption of mixtures of methane, ethane and carbon dioxide (and the corresponding pure gases) was studied using experiment, grand canonical Monte Carlo (GCMC) simulation, and ideal adsorbed solution theory (IAST). Both GCMC and IAST work very well for the adsorption of the methane/ethane mixture in MCM-41. IAST gives good predictions for ethane/carbon dioxide mixture adsorption equilibrium at low and moderate pressures, and exhibits some deviations at relatively high pressures.. AB - We ...

Being secret, the work of von Neumann and Ulam required a code name.[14] A colleague of von Neumann and Ulam, Nicholas Metropolis, suggested using the name Monte Carlo, which refers to the Monte Carlo Casino in Monaco where Ulams uncle would borrow money from relatives to gamble.[12] Using lists of "truly random" random numbers was extremely slow, but von Neumann developed a way to calculate pseudorandom numbers, using the middle-square method. Though this method has been criticized as crude, von Neumann was aware of this: he justified it as being faster than any other method at his disposal, and also noted that when it went awry it did so obviously, unlike methods that could be subtly incorrect. Monte Carlo methods were central to the simulations required for the Manhattan Project, though severely limited by the computational tools at the time. In the 1950s they were used at Los Alamos for early work relating to the development of the hydrogen bomb, and became popularized in the fields of ...

A common managerial problem in the project-based organization is the problem of resource allocation. In practice this problem is addressed by applying project portfolio management. In this study we examine project portfolio management in a consultancy firm by applying a mathematical model. The information produced by this model could enable rational decision making and thus improve the economic resilience and reduce internal uncertainty in the firm so that it may live long and prosper. The proposed model is based on a Markov process that represents the projects in the firm. The parameters are estimated by Maximum Likelihood and the results are estimated through Monte Carlo Simulation.. This study initially shows that it is possible to model the project portfolio as a Markov process. This was supported by the conducted literature review and illustrated by the presented model. Furthermore, we conclude that the value of accepting a project is dependent on the current state of the firm in terms of ...

This thesis consists of the four papers which consider different aspects of stochastic process modeling, error analysis, and minimization of computational cost.. In Paper I, we construct a Multipath Fading Channel (MFC) model for wireless channels with noise introduced through scatterers flipping on and off. By coarse graining the MFC model a Gaussian process channel model is developed. Complexity and accuracy comparisons of the models are conducted.. In Paper II, we generalize a multilevel Forward Euler Monte Carlo method introduced by Mike Giles for the approximation of expected values depending on solutions of Ito stochastic differential equations. Giles work proposed and analyzed a Forward Euler Multilevel Monte Carlo (MLMC) method based on realizations on a hierarchy of uniform time discretizations and a coarse graining based control variates idea to reduce the computational cost required by a standard single level Forward Euler Monte Carlo method. This work is an extension of Giles MLMC ...

... ,Monte Carlo Simulations is MCS is a tool that exploits the Monte Carlo method and with a complex algorithm.

Alexander Shkolnik, CRMR Postdoctoral Scholar, to give contributed session at the MCM 2017 International Conference on Monte Carlo Methods and Applications. Session title: Compactness Approaches for Importance Sampling. From the conference website: "Nine invited plenary speakers will give one-hour talks, with discussion. All other talks will last 30 minutes including questions and discussion. They will be split into sessions of 3 or 4 talks. Some special sessions devoted to a particular topic will be organized by designated or volunteer chairpersons. To promote true exchanges of ideas, it is preferred that all speakers in any given special session have different affiliations, and we will not accept a special session in which more than two speakers have the same affiliation. The other sessions will contain contributed talks accepted on the basis of submitted abstracts".. See the program and event details ». ...

Radiation interaction with matter is by nature stochastic. Monte Carlo simulation makes possible, practical, economical and ethical, many experiments otherwise not. In-silico simulation of random samples of radiation histories places into our hands data which may be treated and analysed in radically different ways. This work reports history-by-history computation of the variance in simulation output from FLUKA, a general-purpose Monte Carlo code. Variance computed history by history is compared with variance estimated from varying batch sizes. This work also addresses the issue of under-sampling where, against conventional expectations, the variance spikes as we sample more histories. The background to the spikes is traced by reconstructing single histories interaction by interaction-a novel level of details atypical of Monte Carlo simulations in the field, where statistical convergence of averaged quantities has been the focus.

inproceedings{391142, author = {Crop, Frederik and Reynaert, Nick and De Gersem, Werner and Pittomvils, Geert and COGHE, MARC and De Neve, Wilfried and Vakaet, Luc and Thierens, Hubert}, booktitle = {RADIOTHERAPY AND ONCOLOGY}, issn = {0167-8140}, language = {eng}, pages = {S419-S419}, publisher = {ELSEVIER IRELAND LTD}, title = {Implementation and validation of an add-on MLC for Monte Carlo dose calculations in conformal stereotactic radiosurgery}, volume = {81}, year = {2006 ...

Downloadable! This paper studies performance of both point and interval predictors of technical inefficiency in the stochastic production frontier model using a Monte Carlo experiment. In point prediction we use the Jondrow et al. (1980) point predictor of technical inefficiency, while for interval prediction the Horrace and Schmidt (1996) and Hjalmarsson et al. (1996) results are used. When ML estimators are used we find negative bias in point predictions. MSEs are found to decline as the sample size increases. The mean empirical coverage accuracy of the confidence intervals are significantly below the theoretical confidence level for all values of the variance ratio.

TY - JOUR. T1 - Incorporation of multivariate statistical distribution of magnitude-distance and Monte-Carlo simulation in probabilistic seismic hazard analysis. AU - Azarbakht, Alireza. AU - Ebrahimi, Mohammad Ali. PY - 2019/7/31. Y1 - 2019/7/31. N2 - The classical seismic hazard analysis is based on two independent simplified assumptions including the statistical distribution of magnitude (usually Gutenberg-Richter 1958) and the distance distribution (equal probability in each point of a given source). However, the interaction between the two distributions is rarely discussed in past researches. Therefore, a joint M-R distribution has been implemented in this paper in order to shed light into these simplified assumptions. The Tehran metropolis is considered as the case study since it locates in a highly active seismic region. Three seismological datasets were used in this study, i.e. the observed dataset, the simulated dataset based on the Han and Choi 2008 methodology, and the simulated ...

Analysis of surface wave data can be made using probabilistic approaches, e.g. Monte Carlo methods that employ a random or pseudo-random generator. A method like this is required to efficiently avoid local minima, evaluate non-uniqueness in the solution and estimating the values and uncertainties of the model parameters. The pure Monte Carlo method applied to surface wave inversion becomes efficient with the introduction of a 'smart sampling' rule which exploits the scale property (scaling of the modal solution with the wavelength) of the solution. Introducing this property in the Monte Carlo inversion focuses the scan of model space on high probability density zones. Each model is scaled before evaluating the misfit in order to bring the theoretical dispersion curve obtained by forward algorithm closer to the experimental. An applicative example is presented to support our hypothesis. <br>The main advantage of the proposed approach, based on scale property of dispersion curves, is the

4 Instituto de Catálisis y Petroleoquímica, CSIC, Cantoblanco, E-28049-Madrid, Spain Abstract The reducibility of molybdenum oxide supported on γ-Al2O3 was studied by temperature programmed reduction (TPR). Interpretation of the reduction profiles was successfully achieved by applying the Monte Carlo method and taking into account the presence of different molybdenum species on the support surface. Seven reactions were assumed to take place along the reduction process. The first hydrogen consumption peak was assigned to the reduction of Mo6+ ions present as well-dispersed polymeric species into Mo+5, while the second one accounts for the reduction not of the Mo5+ ions generated in the first reduction into Mo+4 but also for the reduction of monomeric Mo6+species. Keywords Mo Catalysts. Monte Carlo Method. Temperature Programmed Reduction. I. INTRODUCTION The interaction of molybdenum oxides on the alumina surface and their reduction processes have been extensively investigated as documented in ...

The class was given a graph with the x-axis numbering up to 24. They were required to start at the number 20 and after rolling a six sided dice, subtract the number rolled from 20 and keep rolling until they got to zero. They plotted the numbers they rolled on a graph to see how many turns it took to get to zero. This was done five times for each student. The number of attempts was collected from everyone in class and average was calculated for the number of attempts required for a dice to reduce 20 to zero. The method used in class was a simplistic process of Monte Carlo, in a real life scenario the method is repeated 1,000 or more times to get a better output. Our exercise launched a discussion over the actual value of a monte carlo simulation compared to other forms of regression. We came to the conclusion that Monte Carlo does offer different kinds of answers that could be more valuable in the uncertain world of intelligence analysis. ...

We present a method for restoration of audio which has been distorted by a nonlinear channel or recording medium. We model the signal as a linear process cascaded with a nonlinear distortion. We use sampling methods to perform model selection and parameter estimation. We allow the linear model to be nonstationary, and present results for both synthetic and real distortions.

The present study demonstrates a simulation approach to determine the resources needed to handle urgent surgical cases. We performed a sensitivity analysis and found how wait times change as the result of changing the number of ORs, the service time (e.g., how long resources are devoted to the patient) and surgical volume. The parameters of the program (which is freely available) can be adjusted according to the characteristics of individual hospitals. For example, the number of ORs needed to achieve acceptable wait times will depend on the arrival rate of patients, length of surgical procedures and preparation/clean-up time specific to each hospital.. In the present simulation model the arrival time equates to when the decision is made to perform surgery, and the wait time is the time between the arrival time and when the patient enters the OR. The interpretation of that wait time is made from a clinically relevant perspective, i.e., how long can the patient wait before a further delay would ...

Volumetric calibration is used for high accuracy estimation of the functional volume-to-level relationship for vessels used to store hazardous liquids. An example of calibration of a vessel for reprocessed nuclear material is used to illustrate an analysis of calibration data. We advocate a Bayesian approach, with proper account of genuine prior information, using a reversible jump Markov chain Monte Carlo method for estimation.. ...

Smoothing in state-space models amounts to computing the conditional distribution of the latent state trajectory, given observations, or expectations of fu

July 22, 2014 - Radyalis is showcasing its high-performance Monte Carlo dose calculation product for proton applications simultaneously at the 2014 annual meeting of the American Association of Physics in Medicine (AAPM) in Austin, Texas.. The companys work in large-scale optimization and high-performance computing enables clinicians to utilize the high-accuracy benefits of Monte Carlo at unprecedented speeds for proton therapy dose modeling. The Monte Carlo engine changes radiotherapy workflow as the most complex patient treatment plans can be evaluated for efficacy and biological safety with high confidence in a matter of minutes.. The technology combines new algorithmic and software architecture advances for very high parallel efficiency on customers existing hardware, including single and multiple node installations, clusters and cloud platforms, for both Linux and Windows environments. Radyalis software is highly portable and very flexible, and designed to be integrated via a customer API ...

A process might contain randomness, making it impossible to predict its outcome with certainty. Instead, you can simulate the process. To do this, you have to simulate the randomness, which is what Monte Carlo simulation does. The Excel AnalysisTool Pak Random Number Generation tool is perfect for creating Monte Carlo simulations. Joe shows you how to use this tool to create simulations that use the Discrete distribution. Youll then be able to simulate a variety of processes.

The size dependence of the order-disorder transition in FePt nanoparticles with an L10 structure is investigated by means of Monte Carlo simulations based on an analytic bond-order potential for FePt. A cross parametrization for the Fe-Pt interaction is proposed, which complements existing potentials for the constituents Fe and Pt. This FePt potential properly describes structural properties of ordered and disordered phases, surface energies, and the L10 to A1 transition temperature in bulk FePt. The potential is applied for examining the ordering behavior in small particles. The observed lowering of the order-disorder transition temperature with decreasing particle size confirms previous lattice-based Monte Carlo simulations [M. Müller and K. Albe, Phys. Rev. B 72, 094203 (2005)]. Although a distinctly higher amount of surface induced disorder is found in comparison to previous studies based on lattice-type Hamiltonians, the presence of lattice strain caused by the tetragonal distortion of the L10

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Article Random vibration Monte Carlo simulation using multiple harmonic function schemes. The reliability study of structures under random vibration involves the performance of Monte Carlo simulation in time domain. One important part of such analyse...

The Paperback of the Image Analysis, Random Fields and Dynamic Monte Carlo Methods: A Mathematical Introduction by Gerhard Winkler at Barnes & Noble.

We develop a simple Monte Carlo method to compute the position at a given time of a diffusion on a graph, with constant speed on each edge. This method is exact, and we claim it could be used for simulating the position of a particle in a fissured media. Besides, we advocate that the notion of diffusions on graphs could be useful to understand the behavior of one-dimensional diffusions whose infinitesimal generator has piecewise constant coefficients. ...

Im going to keep this tutorial light on math, because the goal is just to give a general understanding. Monte Carlo methods originated from the Manhattan Project, as a way to simulate the distance neutrons would travel through through various materials [1]. Ideas using sampling had been around for a little while, but they took off…

In the previous post, the value of Pi was approximated by using the Monte Carlo Method. It might be easy to see that the circle-inscribed-in-a -square method used in the project can be generalized to shapes that are highly irregular, like the shape of Texas. ...

Monte Carlo methods for fissured porous media: a gridless approach. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.

Background Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R) methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness) on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set). The original analysis of these data used a linear model (GLS) of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on

We perform successive umbrella sampling grand canonical Monte Carlo computer simulations of the original ST2 model of water in the vicinity of the proposed liquid-liquid critical point, at temperatures above and below the critical temperature. Our results support the previous work of Y. Liu, A. Z. Panagiotop
Physics and chemistry of ice and water

Advances in Quantum Monte Carlo confronts the challenges in quantum mechanics that have become progressively more prevalent in the last five years. This book will cover the needed advances in Quantum Monte Carlo methods including improvements and a complete range of applications. Advances in Quantum Monte Carlo will also include a complete spectrum of applications.

Simulated detection of gamma radiation streaming from a radioactive material shipping cask have been performed with the Monte Carlo codes MCNP4A and MORSE-SGC/S. Despite inherent difficulties in simulating deep penetration of radiation and streaming, the simulations have yielded results that agree within one order of magnitude with the radiation survey data, with reasonable statistics. These simulations have also provided insight into modeling radiation detection, notably on location and orientation of the radiation detector with respect to photon streaming paths, and on techniques used to reduce variance in the Monte Carlo calculations. 13 refs., 4 figs., 2 tabs.

Lets go back to the beginning. There appears to be confusion about the difference between test statistics and methods for computing p-values. As is noted at the beginning of the page [5], the fundamental problem with the paper is that it used a flawed test statistic, not that it used Monte Carlo methods to find the p-value for that flawed statistic. Every hypothesis test uses a test statistic to reduce the data to a single number. The p-value for the test statistic can be calculated analytically (as Ive done for the chi-square test statistic) or by Monte Carlo methods. In the paper, Monte Carlo methods were used to compute the p-value of the "mutation generation" test statistic. The key problem with the analysis from the paper is that it doesnt work to use a weighted average to test for variations in mutation rate. This is like trying to use the sample variance to test for an increase in the mean in Gaussian-distributed data. A statistic should be selected based on the null and alternate ...

The number of applications of the Monte Carlo method in the fields of X-ray imaging and fluorescence has continuously increased over the past two decades, as witnessed by the breathtaking growth of related publications. Developers of Monte Carlo based algorithms/codes as well as their users have produced pioneering results for the prediction of experimental outcomes, the characterization of setups, for dosimetry or even quantification purposes.. During this two-day workshop, the eminent invited speakers below and contributors will disseminate their work through a series of presentations:. - Mateusz Czyzycki (AGH University of Science & Technology, Krakow, and DESY Photon Science, Hamburg ...

Using Kalman techniques, it is possible to perform optimal estimation in linear Gaussian state-space models. We address here the case where the noise probability density functions are of unknown functional form. A flexible Bayesian nonparametric noise model based on Dirichlet process mixtures is introduced. Efficient Markov chain Monte Carlo and Sequential Monte Carlo methods are then developed to perform optimal batch and sequential estimation in such contexts. The algorithms are applied to blind deconvolution and change point detection. Experimental results on synthetic and real data demonstrate the efficiency of this approach in various contexts.

Monte Carlo techniques have been shown to be the most accurate method of modelling radiation transport and dose deposition. With increasingly complex radiotherapy techniques being employed in the continuing fight against cancer, Monte Carlo techniques provide a de finitive method to assess the accuracy of these techniques and the accuracy of the procedures used to test them. This thesis established a method to tune a linear accelerator model, in an efficient process. This model was then employed to examine two techniques used currently in the measurement of the absolute dose for the quality assurance of individual patient IMRT plans ...

Abstract: The control of lipid domain formation in biological membranes has received limited consideration. This mechanism is quantitatively investigated using Monte Carlo computer simulations of a simple model system. Monte Carlo simulations are performed on a simple model system composed of phosphatidylecholine (PC), phosphatidylserine (PS), and cholesterol (Chol). Domain formation induced by binding of the phospholipid binding proteins, annexin A5 (A5) and the C2 protein motif is investigated. Simulations for models containing PC/PS lipids indicate that the addition of A5 does not induce lipid domain formation while binding of C2 greatly induces lipid domain formation. The addition of Chol to PC/PS systems was found to induce lipid demixing in the absence and presence of A5 and further enhance the ability of C2 to form PS domains. Incorporation of a preferential protein-protein interaction to PC/PS and PC/PS/Chol systems was found to further increase lipid demixing for all compositions. Lipid ...

Author: Körmann, F. et al.; Genre: Journal Article; Published in Print: 2010-04-19; Title: Rescaled Monte Carlo approach for magnetic systems: Ab initio thermodynamics of bcc iron

Introduction: In the case of overexposure to ionizing radiation, clinical observations as well as biological and physical dosimetric investigations are usually taken into account to estimate the seriousness of the irradiation. The physical dosimetry can be performed using experimental means, in this case a standard phantom is irradiated under conditions as close as possible to those of the accident, or using simulation techniques based on Monte Carlo calculations. The Monte Carlo method was applied to several radiological accidents occurred during the last years. As an example, the dosimetric reconstruction performed for an accident due to an Iridium 192 industrial source that occurred in Peru in 1999 is presented. Material and Methods: The technique developed in the laboratory, combining the MORSE Monte Carlo code to a Computer-Assisted Design (CAD) software, can assess the absorbed dose in a numerical anthropomorphic model. The CAD software is used to simulate the accident, taking into account ...

The Monte Carlo code MCNP-4B has been utilised to investigate the origins of radiation dose perturbation in the head and neck region, arising from natural heterogeneities, the changing external contours of the patient, boundaries between materials of different atomic number and prosthetic implants. MCNP-4B was used to develop a simple model of a linear accelerator treatment head which incorporated the electron target, primary collimator, beam flattening filter and the secondary collimators. The model was used to calculate the energy spectra and angular distribution of the x-ray beam from a 4 MV Philips SL 75/5 and a 10 MV SL 15, and then tested by using these data to compute the central and off-axis x-ray beam profiles for various field sizes in water. Monte Carlo simulations using the calculated spectra were used to assess the dose distribution of treatment plans obtained in a simple heterogeneous phantom by several commercially available treatment planning systems. Practical measurements were ...

The operation of LITT needs an accurate numerical simulation of laser energy distribution ?? the tissue. Considering the size, the optical property of tumors and their difference from surrounding normal tissue, a two-layer tissue configuration model for LITT is set up, and then energy distribution in the configuration is simulated with Monte Carlo method. On the basis of energy distribution, the steady-state temperature distribution is computed with Pennes equation. All of these will provide an important theoretical guide for clinic application of LITT.

Title: ParDOCK: An All Atom Energy Based Monte Carlo Docking Protocol for Protein-Ligand Complexes. VOLUME: 14 ISSUE: 7. Author(s): A. Gupta, A. Gandhimathi, P. Sharma and B. Jayaram. Affiliation:Dept. of Chemistry&Supercomputing Facility for Bioinformatics&Computational Biology, Indian Institute of Technology, Hauz Khas, New Delhi-110016, India.. Keywords:Energy based scoring, Computer aided drug design (CADD), Monte Carlo docking, Binding affinity, Cluster computing.. Abstract: We report here an all-atom energy based Monte Carlo docking procedure tested on a dataset of 226 proteinligand complexes. Average root mean square deviation (RMSD) from crystal conformation was observed to be ∼ 0.53 Å. The correlation coefficient (r2) for the predicted binding free energies calculated using the docked structures against experimental binding affinities was 0.72. The docking protocol is web-enabled as a free software at www.scfbioiitd. res.in/dock. ...

How is Auxiliary Field Diffusion Monte Carlo abbreviated? AFDMC stands for Auxiliary Field Diffusion Monte Carlo. AFDMC is defined as Auxiliary Field Diffusion Monte Carlo rarely.