Dynamical dosage regimen calculations in linear pharmacokinetics

The objective of this analysis of a linear compartment system is to compute drug input functions that are optimal in producing nontoxic pharmacological responses of maximal therapeutic efficacy. Pharmacokinetics should underlie the rational use of drugs and when a therapeutic range is known, the achievement of safe and effective target concentrations may be assured by a dosage regimen computed for a given administration schedule. The method developed herein is based on linearity and superimposition principles applicable to the class of systems considered. This method requires estimated values of model individual parameters and computes optimum dosage regimens in an iterative scheme, corresponding to a real time dynamical context. An interactive computer program has been developed to perform dosage regimen calculations.     

Acceleration sensitivity of tuning fork gyroscopes: theoretical model,simulation and experimental verification

A two degrees of freedom (DOF) coupled model is investigated in this paper to analyze the acceleration sensitivity of MEMS tuning fork gyroscopes (TFG) and approaches of decreasing the acceleration sensitivity are presented. Since two tines of TFGs are asymmetric in the mass, stiffness and damping caused by the technological defects, there exists the coupled effect between two tines leading to the invalidity of a single DOF model. Therefore, a two DOFs model is established and the matrix perturbation technique is used to calculate the dynamic responses of the two tines by applying the common-mode acceleration. Our quantitative analysis reveals that the displacement difference is large in the in- and anti-phase modal frequencies between two tines, arising from the unsynchronized motion of two tines due to stiffness imbalance. The FEM simulations coincide with our theoretical calculations. Meanwhile, we take advantage of the experimental data from the other researches to verify our theoretical model and analytical expressions. Our results demonstrate that the acceleration sensitivity of TFGs can be reduced by increasing the coupled stiffness ratio, modal frequency and sense beams widths which are insensitive to technological dispersions.     

CAMBIO: software for modelling and simulation of bioprocesses

CAMBIO, a software package devoted to bioprocess modelling, which runs on Apollo computers, is described. This software enables bioengineers to easily and interactively design appropriate mathematical models directly from their perception of the process. CAMBIO provides the user with a set of design symbols and mnemonic icons in order to interactively design a functional diagram. This diagram has to exhibit the most relevant components with their related interactions through biological and physico-chemical reactions. Then, CAMBIO automatically generates the dynamical material balance equations of the process in the form of an algebraic-differential system by taking advantage of the knowledge involved in the functional diagram. The model may be used for control design purpose or completed by kinetics expressions with a view to simulation. CAMBIO offers facilities to generate a simulation model (for coding of kinetics, introducing auxiliary variables, etc.). This model is automatically interfaced with a specialized simulation software which allows an immediate visualization of the process dynamical behaviour under various operational conditions (possibly involving feedback control strategies). An example of an application dealing with yeast fermentation is given.     

Computational challenges in cell simulation: a software engineering approach

Molecular biology's advent in the 20th century has exponentially increased our knowledge about the inner workings of life. We have dozens of completed genomes and an array of high-throughput methods to characterize gene encodings and gene product operation. The question now is how we will assemble the various pieces. In other words, given sufficient information about a living cell's molecular components, can we predict its behavior? We introduce the major classes of cellular processes relevant to modeling, discuss software engineering's role in cell simulation, and identify cell simulation requirements. Our E-Cell project aims to develop the theories, techniques, and software platforms necessary for whole-cell-scale modeling, simulation, and analysis. Since the project's launch in 1996, we have built a variety of cell models, and we are currently developing new models that vary with respect to species, target subsystem, and overall scale.     

A discrete-event simulation and continuous software evaluation on a systemic quality model: An oil industry case

This paper proposes a specific set of criteria for evaluating discrete-event Simulation Software capable of simulating continuous operations. A quality specifications model was developed; it identified 40 sub-characteristics and 131 metrics to assess the quality of this type of software; it is then to be used in the selection process. The application was demonstrated in one organization that provides consulting services in the logistics’ area of the Venezuelan oil industry and it was used to examine four commercial software systems that might fulfill the technical requirements established by the organization. The selection and evaluation technique successfully identified the software that best suited their needs.     

HEpiMA: software for the identification of heterogeneity in meta-analysis

Meta-analysis is a quantitative method available to epidemiologists, psychologists, social scientists and others who wish to produce a summary measure of the effect of exposure on disease, based on results from published studies along with a summary measure of uncertainty. The magnitude of the effect vary from study to study because of differences in the features of these studies (design, population, control of confounding variables etc.). From the various studies an estimator is formed by pooling the results found in each study in one summary measure. This summary (or pooled) measure is meaningful only if the magnitude of heterogeneity between study effects is small and can be explained by sampling variation. In this paper, we present HEpiMA, a new comprehensive and user-friendly software program for epidemiologic meta-analysis. HEpiMA has new features that are not available in other programs. The program carries out a complete study of heterogeneity of study effects with 11 hypothesis test results. In addition to model-based methods, the program also implements bootstrap methodology. New useful estimators of heterogeneity, Ri and CV(B), developed by the authors are given in the output. In addition to these unique features, the major advantage of this software is the option for direct entry of adjusted relative risk estimates of individual studies, the most common form of presentation of results in the epidemiologic literature. This program may also be useful for meta-analysts of clinical trials, in which the relative risk is the parameter of interest as it also allows the entry of crude data under the form of 2x2 tables.     

Clayworks: Toward user-oriented software for collaborative modeling and simulation

We consider the development of software systems that integrate collaborative real-time modeling and distributed computing. Our main goal is user-orientation: we need a collaborative workspace for geographically dispersed users with a seamless access of every user to high-performance servers. This paper presents a particular prototype, Clayworks, that allows modeling of virtual clay objects and running computation-intensive deformation simulations for objects crashing into each other. In order to integrate heterogeneous computational resources, we adopt modern Grid middleware and provide the users with an intuitive graphical interface. Simulations are parallelized using a higher-order component (HOC) which abstracts over the web service resource framework (WSRF) used to interconnect our worksuite to the computation server. Clayworks is a representative of a large class of demanding systems which combine collaborative, user-oriented modeling with performance-critical computations, e.g., crash-tests or simulations of biological population evolution.     

Development,evaluation and benchmarking of simulation software for biomolecule-based computing

Simulators for biomolecular computing, (both in vitro and in silico), have come to play an important role in experimentation, analysis, and evaluation of the efficiency and scalability of DNA and biomolecule based computing. Simulation in silico of DNA computing is useful to support DNA-computing algorithm design and to reduce the cost and effort of lab experiments. Although many simulations have now been developed, there exists no standard for simulation software in this area. Reliability, performance benchmarks, user interfaces, and accessibility are arguably the most important criteria for development and wide spread use of simulation software for BMC. The requirements and evaluation of such software packages for DNA computing software are discussed, particularly questions about software development, appropriate user environments, standardization of benchmark data sets, and centrally available common repositories for software and/or data.     

Regression models for unbalanced longitudinal ordinal data: computer software and a simulation study

A computer program GGOREX in the form of a SAS macro is developed for the analysis of longitudinal ordinal data. It is extended from GEECAT and GEEGOR developed by Williamson, Lipsitz and Kim in their paper in 1999. An illustrative example with some preliminary data from a study conducted by the National Institute of Child Health and Human Development and the University of Alabama at Birmingham is given. Another set of computer programs is developed to make it possible to conduct a simulation study to validate the GGOREX procedure in a finite sample. A simple computer program in FORTRAN using the IMSL software library is developed to solve for the probability distribution of the longitudinal ordinal responses according to the correlation specification.     

In search for a widely applicable and accepted software quality model for software quality engineering

Software Quality Engineering is an emerging discipline that is concerned with improving the approach to software quality. It is important that this discipline be firmly rooted in a quality model satisfying its needs. In order to define the needs of this discipline, the meaning of quality is broadly defined by reviewing the literature on the subject. Software Quality Engineering needs a quality model that is usable throughout the software lifecycle and that it embraces all the perspectives of quality. The goal of this paper is to propose the characteristics of a quality model suitable for such a purpose, through the comparative evaluation of existing quality models and their respective support for Software Quality Engineering.     

Online auctions,messaging, communication and social facilitation: a simulation and experimental evidence

This is a study of social facilitation effects in online auctions. We focus on the growth in online auctions, and the emergence of instant messaging and communication availability technologies. These two trends merge to provide a collaborative online social framework in which computer mediated communication may affect the behaviour of participants in online auctions. The interaction between buyers and sellers in traditional, face-to-face markets creates phenomena such as social facilitation, where the presence of others impacts behaviour and performance. In this study we attempt to replicate and measure social facilitation effects under the conditions of virtual presence. Does social facilitation apply to online auctions, and if so, how can it influence the design of online settings? We developed and used a simulated, Java-based Internet Dutch auction. Our findings indicate that social facilitation does indeed occur. In an experimental examination, participants improve their results and stay longer in the auction under conditions of higher virtual presence. Participants also indicate a preference for auction arrangements with higher degrees of virtual presence. Theoretically, this study contributes to the study of social facilitation, adding evidence of the effect when the presence is virtual.     

Probabilistic model identification of uncertainties in computational models for dynamical systems and experimental validation

We present a methodology to perform the identification and validation of complex uncertain dynamical systems using experimental data, for which uncertainties are taken into account by using the nonparametric probabilistic approach. Such a probabilistic model of uncertainties allows both model uncertainties and parameter uncertainties to be addressed by using only a small number of unknown identification parameters. Consequently, the optimization problem which has to be solved in order to identify the unknown identification parameters from experiments is feasible. Two formulations are proposed. The first one is the mean-square method for which a usual differentiable objective function and an unusual non-differentiable objective function are proposed. The second one is the maximum likelihood method coupling with a statistical reduction which leads us to a considerable improvement of the method. Three applications with experimental validations are presented in the area of structural vibrations and vibroacoustics.     

Automating the simulation of complex discrete-time control systems:a mathematical framework, algorithms, and a software package

With the rapid proliferation of complex control systems, such as adaptive control systems, a need has arisen to automate as much as possible of the time-consuming preparatory work needed to simulate such systems. This burden currently falls on the user. The smaller the user time required and the more effortless the process, the greater, the authors believe, will be the eventual widespread acceptability of these control systems. This paper is aimed at bridging this gap between the theoretical specification of a complex discrete-time control system as described in a typical research paper and the obtaining of a first simulation. It provides a graph theoretical formulation of the issues involved, discrete algorithms to execute these tasks, and finally describes ISIM, an interpretive simulator which incorporates these features. These algorithms automate the simulation process, as seen by the user. The net result is a package which essentially requires only that the user type in a control system more or less verbatim from a technical paper to obtain a simulation output     

Power calculations for generalized linear models in observational longitudinal studies: a simulation approach in SAS

Repeated measurements arising from longitudinal studies occur frequently in applied research. Methods to calculate power in the context of repeated measures are available for experimental settings where the covariate of interest is a discrete treatment indicator. However, no closed form expression exists to calculate power for generalized linear models with non-zero within-cluster correlation that are common in epidemiological and observational studies in which the covariate of interest varies over time and is often measured on a continuous scale, and where the researchers control for several potential confounders. We describe a Monte Carlo simulation approach conducted to calculate power, and illustrate its application in two models frequently encountered in practice, the normal linear mixed model, and the logistic regression model, both with repeated measurements and non-zero within-cluster correlation. This approach can be used to calculate the effect on power of changing various simulation conditions controlled by the researcher, such as sample size, within-cluster correlation structure, smallest meaningful difference to detect, and distributional assumptions.     

Generic model identification framework for thermodynamic engines for use in hybrid power stations control and simulation

Thermodynamic engines are focusing increasing attention in the context of solar-based electric power generation. Knowledge-based models of such engines are sometimes difficult to derive and when they are available, their simulation may be numerically a rather heavy task given the control updating period that may be needed. In the present work a generic nonlinear identification framework that enables the dynamics of the key quantities of a thermodynamic engine to be captured is proposed. Such a fast model can then be used in the simulation and the control design stage of the whole electric power generation station. The proposed identification framework is validated on a recently developed knowledge-based model of a beta-type Stirling engine with rhomic-drive mechanism.     

Calibrating a software cost estimation model: why and how

Calibration, has been found to be difficult in practice. Wide experience in using the estimation model is necessary; experience which the beginner naturally lacks. This paper indicates why it is important to calibrate a model and how the inexperienced user can be helped by an expert system. In addition, the development of, and experience with, the prototype of an expert system are described. The system dealt with here is intended for the calibration of the PRICE SP estimation.     

卫星GN&C分系统建模与仿真软件实现

卫星系统的总体设计以及在轨运行等任务都离不开对其制导、导航与控制(GN&C)分系统的设计、优化与仿真演示,但GN&C分系统方案以及算法的复杂性对于GN&C分系统的快速设计、仿真与决策非常不利.采用Matlab/Simulink作为后台计算引擎、利用Matlab与VC混合编程,设计实现了一个卫星GN&C分系统建模与仿真软件环境.该软件环境能够屏蔽GN&C分系统的构建细节从而快速搭建具体的仿真应用,可实现对卫星GN&C分系统方案的快速仿真评估,并实现建模环境与具体的仿真应用相分离.