MARLIN, software to create, run, and analyse spatially realistic simulations

MARLIN is a software to create, run, analyse, and visualize spatially explicit population genetic simulations. It provides an intuitive user interface with which the geographical layout of a metapopulation can be drawn by hand or loaded from a map. Furthermore, the interface allows easy selection of the many different simulation settings. MARLIN then uses the program QuantiNemo to run the simulation in the background. When simulations are finished, MARLIN directly analyses and plots the results, thereby greatly simplifying the simulation workflow. This combination of simulation and analysis makes MARLIN ideal for teaching and for scientists who are interested in doing simulations without having to learn command-line operations. MARLIN is available for computers running Mac OS X and can be downloaded from: http://www.patrickmeirmans.com/software.     

On the interpretation of biochemical data by molecular dynamics computer simulation.

The application of computer simulation to molecular systems of biochemical interest is reviewed. It is shown that computer simulation is a tool complementary to experimental methods, which can be used to access atomic details inaccessible to experimental probes. Examples are given in which computer simulation augments the experimental information by providing an atomic picture of high resolution with respect to space, energy or time. The usefulness of a computer simulation largely depends on its quality. The most important factors that limit the accuracy of simulated results are discussed. The accuracy of different simulation studies can differ by orders of magnitude. The accuracy will depend on the type of biomolecular system and process studied. It will also depend on the choice of force field, the simulation set-up and the protocol that is used. A list of quality-determining factors is given, which may be useful when interpreting simulation studies appearing in the literature.     

Practical aspects of Monte Carlo simulation of charged particle transport: Mixed algorithms and variance reduction techniques

This paper is concerned with the practical implementation of Monte Carlo simulation methods for charged particle transport. The emphasis is on light particles (electrons and positrons) because of the larger scattering and energy straggling effects. Differential cross sections (DCS) for the various interaction mechanisms are described. As the average number of interactions along the particle track increases with the initial energy, detailed simulation becomes unfeasible at high energies. We can then rely on mixed simulation algorithms: hard events (i.e. individual interactions with angular deflection or energy loss larger than given cutoff values) are sampled from the DCS whereas soft events are simulated by means of a multiple scattering approach. Too frequently, the statistical uncertainty of analogue simulation (i.e. strict simulation of the physical interaction process) is found to be so large that results are meaningless. This problem can be partially solved by applying simple variance reduction techniques. Received: 10 September 1998 / Accepted in revised form: 10 November 1998     

Branching patterns: the simulation of plant architecture

This article describes a basis for the simulation of plant growth in “architectural” terms. Architecture is used here in a design rather than mechanical sense.The form of the plant is governed by the organized pattern of its branching. A plant is considered to be built up of a series of shoot-units. Each shoot-unit is the product of the activity of a single apical meristem (which may remain dormant for a time as a bud). The architecture of the plant is described in numerical file form in terms of “rules of growth”, governing shoot-unit types, and their capacity to bear daughter units. A computer programme utilizes any given pattern data file to activate the developmental branch growth of the plant on a visual display screen. The process is recursive. The format of 2D pattern data files is described with examples, and indicates an extension to 313, and to the simulation of seed dispersal.The system can be operated in an empirical or intuitive manner. In the former case, the details of the simulation are based on measurements of plants in the field and lead to a graphical prediction of the range of architecture possible for the given species. In the second case, the data on which the simulation is based is entirely subjective, details being adjusted until the graphic representation appears accurate when compared with actual plants. Subjective simulation may be confirmed subsequently by field observation.The strength of this simulation procedure lies in the close relationship between its constructional basis and that of the plant. Therefore the quantitative and qualitative information inherent in the control of any particular simulation is inevitably directly related to that of the plant. The architectural response to physical or genetical manipulation of the plant can be predicted because changes made in the parameters of a particular simulation reflect parallel changes to be expected of the real plant. It thus becomes possible to provide a measure of the essential elements that underlie the form and shape of any plant.     

Tolerance Analysis for Design of Multistage Manufacturing Processes Using Number-Theoretical Net Method (NT-net)

Recent developments in modeling stream of variation in multistage manufacturing system along with the urgent need for yield enhancement in the semiconductor industry has led to complex large scale simulation problems in design and performance prediction, thus challenging current Monte Carlo (MC) based simulation techniques. MC method prevails in statistical simulation approaches for multi-dimensional cases with general (i.e., non-Gaussian) distributions and/or complex response functions. A method is proposed based on number theory (NT-net) to reduce computing effort and the variability of MC's results in tolerance design and circuit performance simulation. The sampling strategy is improved by introducing NT-net that can provide better convergent rate over MC. The new method is presented and verified using several case studies, including analytical and industrial cases of a filter design and analyses of a four-bar mechanism. Results indicate a 90–95% reduction of computation effort with significant improvement in accuracy that can be achieved by the proposed technique.     

Computer simulation is an undervalued tool for genetic analysis: a historical view and presentation of SHIMSHON--a Web-based genetic simulation package

Computer simulation methods are under-used tools in genetic analysis because simulation approaches have been portrayed as inferior to analytic methods. Even when simulation is used, its advantages are not fully exploited. Here, I present SHIMSHON, our package of genetic simulation programs that have been developed, tested, used for research, and used to generated data for Genetic Analysis Workshops (GAW). These simulation programs, now web-accessible, can be used by anyone to answer questions about designing and analyzing genetic disease studies for locus identification. This work has three foci: (1) the historical context of SHIMSHON's development, suggesting why simulation has not been more widely used so far. (2) Advantages of simulation: computer simulation helps us to understand how genetic analysis methods work. It has advantages for understanding disease inheritance and methods for gene searches. Furthermore, simulation methods can be used to answer fundamental questions that either cannot be answered by analytical approaches or cannot even be defined until the problems are identified and studied, using simulation. (3) I argue that, because simulation was not accepted, there was a failure to grasp the meaning of some simulation-based studies of linkage. This may have contributed to perceived weaknesses in linkage analysis; weaknesses that did not, in fact, exist.     

A statistical simulation model for field testing of non‐target organisms in environmental risk assessment of genetically modified plants

Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non‐target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess‐zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided.     

Power calculations for a general class of family-based association tests: dichotomous traits

Using large-sample theory, we present a unified approach to power calculations for family-based association tests. Currently available methods for power calculations are restricted to special designs or require approximations or simulations. Our analytical approach to power calculations is broadly applicable in many settings. We discuss power calculations for two scenarios that have high practical relevance and in which power previously could only be assessed by simulation studies or by approximations: (1) studies using both affected and unaffected offspring and (2) studies with missing parental information. When the population prevalence is high, it can be worthwhile to genotype unaffected offspring. For many scenarios, high power can be achieved with reasonable sample sizes, even when no parental information is available.     

鄂尔多斯高原生态过渡带的判定及生物群区特征

 本文用Holdridge生命地带方法对鄂尔多斯高原的生物群区进行了分类研究,研制了用于生态过渡带判定的计算机模型,模拟结果与实际情况基本吻合。鄂尔多斯高原的生物群区可分为草原、荒漠灌丛和荒漠3大类,草原群区以本氏针茅(Stipa bungeana)群落为主,荒漠灌丛群区以冷蒿(Artemisia frigida),狭叶锦鸡儿(Caragana stenophylla)群落为主,荒漠群区以红砂(Reaumuria soongorica)群落为主。鄂尔多斯高原的地带性植被在传统上分为典型草原、荒漠草原和草原化荒漠3部分,在典型草原的边界划分上,传统划分与本文结果一致。而在荒漠草原和草原化荒漠的边界方面,模拟结果与传统划分有一定的差异。荒漠灌丛和荒漠草原以及荒漠和草原化荒漠在生物群落特征上具有一定的相似性,荒漠灌丛和荒漠在生态特征上较荒漠草原和草原化荒漠更为旱化,在地理位置上更为靠西部。该计算机模型结合了地理空间分析,能准确地确定生态过渡带的位置和宽度,为研究鄂尔多斯高原生态过渡带的特征提供了较可靠的技术手段。     

Simulation Architecture for Modelling Interaction Between User and Elbow-articulated Exoskeleton

The aim of our work is to improve the existing user-exoskeleton models by introducing a simulation architecture that can simulate its dynamic interaction,thereby altering the initial motion of the user.A simulation architecture is developed that uses the musculoskeletal models from OpenSim,and that implements an exoskeleton control algorithm and human response model in Matlab.The musculoskeletal models need to be extended with the response of a user to external forces to simulate the dynamic interaction.A set of experiments was performed to fit this response model.A validation test showed that more than 80％ of the variance of the motion could be explained.With the human response model in the combined simulation architecture,asimulation in which an object connects with the exoskeleton or with the human is performed.The effect of the exoskeleton on,among others,muscle excitation and altered motion can be assessed with this architecture.Our work can be used to better predict the effect an exoskeleton has on the user.     

Fast digital simulation of spiking neural networks and neuromorphic integration with SPIKELAB

We present a simulation environment called SPIKELAB which incorporates a simulator that is able to simulate large networks of spiking neurons using a distributed event driven simulation. Contrary to a time driven simulation, which is usually used to simulate spiking neural networks, our simulation needs less computational resources because of the low average activity of typical networks. The paper addresses the speed up using an event driven versus a time driven simulation and how large networks can be simulated by a distribution of the simulation using already available computing resources. It also presents a solution for the integration of digital or analogue neuromorphic circuits into the simulation process.     

Linkage studies on Gilles de la Tourette syndrome: what is the strategy of choice?

For a linkage study it is important to ascertain family material that is sufficiently informative. The statistical power of a linkage sample can be determined via computer simulation. For complex traits uncertain parameters such as incomplete penetrance, frequency of phenocopies, gene frequency and variable expression have to be taken into account. One can either include only the most severe phenotype in the analysis or apply multiple linkage tests for a gradually broadened disease phenotype. Gilles de la Tourette syndrome (GTS) is a chronic neurological disorder characterized by multiple, intermittent motor and vocal tics. Segregation analyses suggest that GTS and milder phenotypes are caused by a single dominant gene. We report here the results of an extensive simulation study on a large set of families. We compared the effectiveness of linkage tests with only the GTS phenotype versus multiple tests that included various milder phenotypes and different gene frequencies. The scenario of multiple tests yielded superior power. Our results show that computer simulation can indicate the strategy of choice in linkage studies of multiple, complex phenotypes.     

Tie trees generated by distance methods of phylogenetic reconstruction

In examining genetic data in recent publications, Backeljau et al. showed cases in which two or more different trees (tie trees) were constructed from a single data set for the neighbor-joining (NJ) method and the unweighted pair group method with arithmetic mean (UPGMA). However, it is still unclear how often and under what conditions tie trees are generated. Therefore, I examined these problems by computer simulation. Examination of cases in which tie trees occur shows that tie trees can appear when no substitutions occur along some interior branch(es) on a tree. However, even when some substitutions occur along interior branches, tie trees can appear by chance if parallel or backward substitutions occur at some sites. The simulation results showed that tie trees occur relatively frequently for sequences with low divergence levels or with small numbers of sites. For such data, UPGMA sometimes produced tie trees quite frequently, whereas tie trees for the NJ method were generally rare. In the simulation, bootstrap values for clusters (tie clusters) that differed among tie trees were mostly low (< 60%). With a small probability, relatively high bootstrap values (at most 70%-80%) appeared for tie clusters. The bias of the bootstrap values caused by an input order of sequence can be avoided if one of the different paths in the cycles of making an NJ or UPGMA tree is chosen at random in each bootstrap replication.      

Modeling FMS with decision Petri nets

Decision point extended timed Petri nets or decision Petri nets (DPN) are introduced as an extended modeling framework for FMS performance evaluation. The decision point extension allows the explicit modeling of the control of the flow of tokens in timed Petri nets and hence represents the control of the flow of material, resources, and information in FMS. Further, the concept of a bounded transition is proposed to conveniently model the blocking logic in an FMS with limited buffer capacities. The motivation to present these conventions is to develop a user-friendly graphic model to represent FMS designs for analysis by discrete event simulation. DPN affords concise models that can be conveniently developed and easily transformed into discrete event simulation models. With the help of a simple FMS example, which includes a number of part types, loading rules, dispatching rules, and probabilistic branching (at an inspection station), we illustrate the DPN model development. As an illustration of the ease with which it can be tranformed into a simulation model, we have developed a generalized simulator called ROBSIM and outline here its methodological basis. The proposed concepts should be of interest to users of discrete event simulation in FMS design or elsewhere to tap the potential of basic Petri net concepts for graphic representation and specification purposes. In particular, our work should encourage other researchers to develop extensions relevant to their own areas of interest.     

QSim, a program for NMR simulations

We present QSim, a program for simulation of NMR experiments. Pulse sequences are implemented and analyzed in QSim using a mouse driven interface. QSim can handle almost any modern NMR experiment, using multiple channels, shaped pulses, mixing, decoupling, phase-cycling and pulsed field gradients. Any number of spins with any spin quantum number can, in theory, be used in simulations. Relaxation is accounted for during all steps of pulse sequences and relaxation interference effects are supported. Chemical kinetics between any numbers of states can be simulated. Both classical and quantum mechanical calculations can be performed. The result of a simulation can be presented either as magnetization as a function of time or as a processed spectrum.     

A Mathematical Framework for Modeling Axon Guidance

In this paper, a simulation tool for modeling axon guidance is presented. A mathematical framework in which a wide range of models can been implemented has been developed together with efficient numerical algorithms. In our framework, models can be defined that consist of concentration fields of guidance molecules in combination with finite-dimensional state vectors. These vectors can characterize migrating growth cones, target neurons that release guidance molecules, or other cells that act as sources of membrane-bound or diffusible guidance molecules. The underlying mathematical framework is presented as well as the numerical methods to solve them. The potential applications of our simulation tool are illustrated with a number of examples, including a model of topographic mapping.     

Simulation of bone adaptive remodeling using a stochastic process as loading history

In this simulation study for bone adaptive remodeling, loading conditions are described as stochastic processes to catch the unpredictable characteristics of daily physical activities, which are observed to be closely related with bone adaptive remodeling. This will not only eliminate the necessity of arbitrary choices for loading conditions, but also generate greater flexibility for simulations of bone adaptive remodeling. The sensitivity of simulation outcomes to the parameters in the simulation algorithm was examined by applying stochastic loading conditions on finite element models of simplified spine structures. In this way, the limitations induced by simplifying loading conditions into constant or cyclic loads can be avoided and, potentially, more clinical observations could be accommodated when more comprehensive finite element models are available.     

Testing for group effect in a 2 x k heteroscedastic ANOVA model

It is natural to want to relax the assumption of homoscedasticity and Gaussian error in ANOVA models. For a two-way ANOVA model with 2 x k cells, one can derive tests of main effect for the factor with two levels (referred to as group) without assuming homoscedasticity or Gaussian error. Empirical likelihood can be used to derive testing procedures. An approximate empirical likelihood ratio test (AELRT) is derived for the test of group main effect. To approximate the distributions of the test statistics under the null hypothesis, simulation from the approximate empirical maximum likelihood estimate (AEMLE) restricted by the null hypothesis is used. The homoscedastic ANOVA F -test and a Box-type approximation to the distribution of the heteroscedastic ANOVA F -test are compared to the AELRT in level and power. The AELRT procedure is shown by simulation to have appropriate type I error control (although possibly conservative) when the distribution of the test statistics are approximated by simulation from the constrained AEMLE. The methodology is motivated and illustrated by an analysis of folate levels in the blood among two alcohol intake groups while accounting for gender.     

3D Profile Simulation of Metal Nanostructures Obtained by Closely Packed Nanosphere Lithography

Closely packed lithography is a versatile technology to fabricate different kinds of periodically arranged nanostructures on substrate or in solution. Due to its large diversities and versatilities, it is necessary to predict the shape of the nanostructures under various fabrication conditions. This paper gives a full simulation for the profile of metal nanostructures fabricated by closely packed nanosphere lithography. The simulation applies to both hexagonal and quadrangular nanosphere arrangements, and the nanospheres can be in one layer or stacked in two layers, with each layer having a different size. For metal evaporated at any angle onto the nanosphere mask, three-dimensional metal nanostructures on each layer of the nanosphere as well as the substrate are given. The simulation helps to obtain the desired metal nanostructures by predicting the profiles and facilitating the process design in closely packed lithography, and it is especially beneficial for finding out the profiles of the nanostructures hidden under the nanospheres, which are undetectable without removing the nanosphere layers.