Understanding how a protein folds is a long-standing challenge in modern science. We have used an optimized atomistic model (united-residue force field) to simulate folding of small proteins of various structures: HP-36 (alpha protein), protein A (beta), 1fsd (alpha+beta), and betanova (beta). Extensive Monte Carlo folding simulations (ten independent runs with 10(9) Monte Carlo steps at a temp...

We show how Monte Carlo and related methods as complete enumeration can help to predict and understand the outcomes of concrete biophysical experiments. Three examples are discussed: the eeect of glycosylation on conformational distributions of peptides, the folding of an-helical hairpin model protein, and the structure of a longer cycloamy-lose. One of the major factors hampering the use of Mo...

We have used Monte Carlo methods and analytical techniques to investigate the influence of the characteristics, such as pipe length, diffusion, adsorption, desorption, and reaction rates on the transient properties of single-file systems. The transient or the relaxation regime is the period in which the system is evolving to equilibrium. We have studied the system when all the sites are reactiv...

A computer model for an Electron Cyclotron Resonance Ion Source (ECRIS) plasma is under development that currently incorporates non-Maxwellian distribution functions, multiple atomic species, and ion confinement due to the ambipolar potential that arises from fast electrons. Atomic processes incorporated into the model include multiple ionization and multiple charge-exchange with rate coefficie...

Monte Carlo simulation is fast becoming the technology of choice for evaluating and analyzing assets, be it pure financial derivatives or investments in real assets. Two of the main virtues of simulation are flexibility and simplicity. There is no constraint on the type of uncertainty that can be modeled and most any type of decision rule can be incorporated. Simulation is also easy to implemen...

Monte Carlo simulation is mainly done in computer clusters, supercomputers or computers coupled with hardware accelerators. These processing methods are sufficiently fast; however, this speed comes at the expense of physical area and power consumption. The current study aims to use System-OnProgrammable-Chip (SOPC) to accomplish the same task but using a smaller physical area. The SOPC approach...

This paper surveys recent research on using Monte Carlo techniques to improve quasi-Monte Carlo techniques. Randomized quasi-Monte Carlo methods provide a basis for error estimation. They have, in the special case of scrambled nets, also been observed to improve accuracy. Finally through Latin supercube sampling it is possible to use Monte Carlo methods to extend quasi-Monte Carlo methods to hi...

monte carlo simulation is a standard technique for project risk analysis. however, some assumptions of this technique are not reasonable in real world. when a project falls behind the schedule, managers take actions to improve the performance. nevertheless, most of the simulation models as monte carlo omit these reactions in their analysis, which results in unreasonable wide distributions or ev...