Monte Carlo simulation of streamflow of the Salt River, Arizona

EXTRACT (SEE PDF FOR FULL ABSTRACT): Evaluations of the impact of climate change (such as a greenhouse effect) upon water resources should represent both the expected change and the uncertainty in that expectation. Since water resources such as streamflow and reservoir levels depend on a variety of factors, each of which is subject to significant uncertainty, it is desirable to formulate methods of representing that uncertainty in the forcing factors and from this determine the uncertainty in the response variables of interest. We report here progress in the representation of the uncertainty in climate upon the uncertainty in the estimated hydrologic response.

Blind equalization and sequence estimation using Markov chain Monte Carlo methods

This paper discusses the problem of restoring a digital input signal that has been degraded by an unknown FIR filter in noise, using the Gibbs sampler. A method for drawing a random sample of a sequence of bits is presented; this is shown to have faster convergence than a scheme by Chen and Li, which draws bits independently. ©1998 IEEE.

重组竹叶青蛇毒纤溶酶原激活剂TSV-PA效应观察体内溶栓

】目的观察重组竹叶青蛇毒纤溶酶原激活剂一体内溶栓效应。方法利用家兔制备的脑血检 模型, 以生理盐水和尿激酶为对照, 用数字减影血管造影技术观察重组竹叶青蛇毒纤溶酶原激活剂飞体内溶 检效果。结果昭高剂量实验组喇再通时间为以内月州低剂量实验组止以内再 通。尿激酶组以刃再通时间为一以内生理盐水对照组没有观察到再通现象。实验动物后处 死解剖, 未观察到出血现象和其它异常现象。结论重组巧勺一在体内具有良好的溶检活性。

An overview of Sequential Monte Carlo methods for parameter estimation in general state-space models

Nonlinear non-Gaussian state-space models arise in numerous applications in control and signal processing. Sequential Monte Carlo (SMC) methods, also known as Particle Filters, provide very good numerical approximations to the associated optimal state estimation problems. However, in many scenarios, the state-space model of interest also depends on unknown static parameters that need to be estimated from the data. In this context, standard SMC methods fail and it is necessary to rely on more sophisticated algorithms. The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed to perform static parameter estimation in general state-space models. We discuss the advantages and limitations of these methods. © 2009 IFAC.

A markov chain Monte Carlo method for estimating population mixing using Y-chromosome markers: Mixing of the Han people in China

We present a new approach for estimating mixing between populations based on non-recombining markers, specifically Y-chromosome microsatellites. A Markov chain Monte Carlo (MCMC) Bayesian statistical approach is used to calculate the posterior probability

B itte r an d Sw e e t /Um am i Ta s te Re c ep to rs w ith D iffe ren tly Evo lu tio n a ry Pa thw ays

通过生物信息学和系统发育学分析,研究了苦味受体和甜味/鲜味受体的进化途径。结果显示,苦味受体 和甜味/鲜味受体在进化上具有远相关,并且具有不同的进化途径,提示这可能是导致这些受体具有不同功能,传 导不同味觉的原因。

Monte Carlo optimization strategies for air-traffic control

The safety of the flights, and in particular conflict resolution for separation assurance, is one of the main tasks of Air Traffic Control. Conflict resolution requires decision making in the face of the considerable levels of uncertainty inherent in the motion of aircraft. We present a Monte Carlo framework for conflict resolution which allows one to take into account such levels of uncertainty through the use of a stochastic simulator. A simulation example inspired by current air traffic control practice illustrates the proposed conflict resolution strategy. Copyright © 2005 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

生物分子水溶液的Monte Carlo模拟 Ⅲ: 力偏倚抽样法和Metropolis抽样法的比较

用力偏倚(FB)法,由体系的晶体点阵构型出发到达平衡态所需的循环数为Metroplis法的武分之二。为了得到较好的结构信息所需的构型数也仅为后者的五分之二。虽然每个循环所需机时为Metropolis法的1.6倍,仍是一加速收敛的好方法。此外进一步支持了以分子的平移扩散作为判别抽样效率的判据,指出接受几率在0.33—0.36之间的步长可能是合适的。此外还统计了和丙氨酸作用大于2kcal/mol的分子座标,使它们与丙氨酸-水分子径向分布图的峰值相对应。图2表2参9