Modeling and simulation for individualized therapy of amisulpride in Chinese patients with schizophrenia:focus on inter interindi⁃vidual variability,therapeutic reference range and laboratory alert level

OBJECTIVE To explain the high inter-individual variability and the frequency of exceeding the therapeutic reference range and the laboratory alert level of amisulpride,a popula⁃tion pharmacokinetic model in Chinese patients with schizophrenia was built based on therapeu⁃tic drug monitoring data to guide individualized therapy.METHODS Plasma concentration data(330 measurements from 121 patients)were ana⁃lyzed using a nonlinear mixed-effects model⁃ing approach with first-order conditional estima⁃tion with interaction(FOCE I).The concentra⁃tions of amisulpride were detected by HPLC-MS/MS.Age,weight,sex,combination medication history and renal function status were evaluated as main covariates.The model was internally val⁃idated using goodness-of-fit,bootstrap and nor⁃malized prediction distribution error.Recom⁃mended dosage regimens for patients with key covariates were estimated on the basis of Monte Carlo simulations and the established model.RESULTS A one-compartment model with first-order absorption and elimination was found to adequately characterize amisulpride concentra⁃tion in Chinese patients with schizophrenia.The population estimates of the apparent volume of distribution(V/F)and apparent clearance(CL/F)were 12.7 L and 1.12 L·h-1,respectively.Age sig⁃nificantly affected the clearance of amisulpride and the final model was as follow:CL/F=1.04×(AGE/32)-0.624(L·h-1).To avoid exceeding the lab⁃oratory alert level(640μg·L-1),the model-based simulation results showed that the recommended dose of amisulpride was no more than 600 mg per day for patients aged 60 years,800 mg per day for those aged 40 years and 1200 mg per day for those aged 20 years,respectively.CON⁃CLUSION Dosage optimization of amisulpride can be carried out according to age to reduce the risk of adverse reactions.The model can be used as a suitable tool for designing individual⁃ized therapy for Chinese patients with schizo⁃phrenia.

A Numerical Convex Lens for the State-Discretized Modeling and Simulation of Megawatt Power Electronics Systems as Generalized Hybrid Systems

Modeling and simulation have emerged as an indispensable approach to create numerical experiment platforms and study engineering systems.However,the increasingly complicated systems that engineers face today dramatically challenge state-of-the-art modeling and simulation approaches.Such complicated systems,which are composed of not only continuous states but also discrete events,and which contain complex dynamics across multiple timescales,are defined as generalized hybrid systems(GHSs)in this paper.As a representative GHS,megawatt power electronics(MPE)systems have been largely integrated into the modern power grid,but MPE simulation remains a bottleneck due to its unacceptable time cost and poor convergence.To address this challenge,this paper proposes the numerical convex lens approach to achieve state-discretized modeling and simulation of GHSs.This approach transforms conventional time-discretized passive simulations designed for pure-continuous systems into state-discretized selective simulations designed for GHSs.When this approach was applied to a largescale MPE-based renewable energy system,a 1000-fold increase in simulation speed was achieved,in comparison with existing software.Furthermore,the proposed approach uniquely enables the switching transient simulation of a largescale megawatt system with high accuracy,compared with experimental results,and with no convergence concerns.The numerical convex lens approach leads to the highly efficient simulation of intricate GHSs across multiple timescales,and thus significantly extends engineers’capability to study systems with numerical experiments.

Dynamics modeling and simulation of mechanism with joint clearance

The existence of clearance in the joints of mechanisms system is inevitable.The movements of the real mechanism are deflection from the ideal mechanism due to the clearances and the motion accuracy is decreased.The effects of the hinge clearance on the crank and rocker mechanism system are studied.The system dynamics equation with clearance is presented.The contact dynamics model is established using the nonlinear equivalent spring-damp model and the friction effect is considered by using Coulomb friction model.Then the models are incorporated into ADAMS,and based on the model,large numbers numeric simulations are made.The regularity of contact forces in clearance are studied in detail.And the effects of clearance size,clearance friction on the mechanism dynamics characteristic are analyzed.The simulation results can predict the effects of clearance on the mechanism dynamics characteristic preferably.

Conceptual Modeling and Simulation Application Analysis of In-service Assessment

Firstly,this paper expounds the conceptual connotation of inservice assessment in the new system,then applies modeling and Simulation in the field of in-service assessment,establishes the conceptual model of inservice assessment and its process,and finally analyzes the application of modeling and simulation in the specific links of in-service assessment.

Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

Modeling and Simulation of Cooperative Exploration Strategies in Unknown Environments

Cooperative spatial exploration in initially unknown surroundings is a common embodied task in various applications and requires satisfactory coordination among the agents.Unlike many other research questions,there is a lack of simulation platforms for the cooperative exploration problem to perform and statistically evaluate different methods before they are deployed in practical scenarios.To this end,this paper designs a simulation framework to run different models,which features efficient event scheduling and data sharing.On top of such a framework,we propose and implement two different cooperative exploration strategies,i.e.,the synchronous and asynchronous ones.While the coordination in the former approach is conducted after gathering the perceptive information from all agents in each round,the latter enables an ad-hoc coordination.Accordingly,they exploit different principles for assigning target points for the agents.Extensive experiments on different types of environments and settings not only validate the scheduling efficiency of our simulation engine,but also demonstrate the respective advantages of the two strategies on different metrics.

Geographic modeling and simulation systems for geographic research in the new era: Some thoughts on their development and construction

Regionality,comprehensiveness,and complexity are regarded as the basic characteristics of geography.The exploration of their core connotations is an essential way to achieve breakthroughs in geography in the new era.This paper focuses on the important method in geographic research:Geographic modeling and simulation.First,we clarify the research requirements of the said three characteristics of geography and its potential to address geo-problems in the new era.Then,the supporting capabilities of the existing geographic modeling and simulation systems for geographic research are summarized from three perspectives:Model resources,modeling processes,and operational architecture.Finally,we discern avenues for future research of geographic modeling and simulation systems for the study of regional,comprehensive and complex characteristics of geography.Based on these analyses,we propose implementation architecture of geographic modeling and simulation systems and discuss the module composition and functional realization,which could provide theoretical and technical support for geographic modeling and simulation systems to better serve the development of geography in the new era.

Safety modeling and simulation of multi-factor coupling heavy-equipment airdrop

Heavy-equipment airdrop is a highly risky procedure that has a complicated system due to the secluded and complex nature of factors＇ coupling. As a result, it is difficult to study the modeling and safety simulation of this system. The dynamic model of the heavy-equipment airdrop is based on the Lagrange analytical mechanics, which has all the degrees of freedom and can accurately pinpoint the real-time coordinates and attitude of the carrier with its cargo. Unfavorable conditions accounted in the factors＇ models, including aircraft malfunctions and adverse environments, are established from a man-machine-environment perspective. Subsequently, a virtual simulation system for the safety research of the multi-factor coupling heavy-equipment airdrop is developed through MATLAB/Simulink, C language and Flightgear software. To verify the veracity of the theory, the verification model is built based on dynamic software ADAMS. Finally, the emulation is put to the test with the input of realistic accident variables to ascertain its feasibility and validity of this method.

Modeling and simulation of chemically reacting flows in gas-solid catalytic and non-catalytic processes

This paper gives an overview of the recent development of modeling and simulation of chemically react- ing flows in gas-solid catalytic and non-catalytic processes. General methodology has been focused on the Eulerian-Lagrangian description of particulate flows, where the particles behave as the catalysts or the reactant materials. For the strong interaction between the transport phenomena （i.e., momentum, heat and mass transfer） and the chemical reactions at the particle scale, a cross-scale modeling approach, i.e., CFD-DEM or CFD-DPM, is established for describing a wide variety of complex reacting flows in multiphase reactors, Representative processes, including fluid catalytic cracking （FCC）, catalytic conversion of syngas to methane, and coal pyrolysis to acetylene in thermal plasma, are chosen as case studies to demonstrate the unique advantages of the theoretical scheme based on the integrated particle-scale information with clear physical meanings, This type of modeling approach provides a solid basis for understanding the multiphase reacting flow problems in general.

Agent-based Modeling and Simulation for the Electricity Market with Residential Demand Response

Currently,critical peak load caused by residential customers has attracted utility companies and policymakers to pay more attention to residential demand response(RDR)programs.In typical RDR programs,residential customers react to the price or incentive-based signals,but the actions can fall behind flexible market situations.For those residential customers equipped with smart meters,they may contribute more DR loads if they can participate in DR events in a proactive way.In this paper,we propose a comprehensive market framework in which residential customers can provide proactive RDR actions in a day-ahead market(DAM).We model and evaluate the interactions between generation companies(GenCos),retailers,residential customers,and the independent system operator(ISO)via an agent-based modeling and simulation(ABMS)approach.The simulation framework contains two main procedures—the bottom-up modeling procedure and the reinforcement learning(RL)procedure.The bottom-up modeling procedure models the residential load profiles separately by household types to capture the RDR potential differences in advance so that residential customers may rationally provide automatic DR actions.Retailers and GenCos optimize their bidding strategies via the RL procedure.The modified optimization approach in this procedure can prevent the training results from falling into local optimum solutions.The ISO clears the DAM to maximize social welfare via Karush-Kuhn-Tucker(KKT)conditions.Based on realistic residential data in China,the proposed models and methods are verified and compared in a large multi-scenario test case with 30,000 residential households.Results show that proactive RDR programs and interactions between market entities may yield significant benefits for both the supply and demand sides.The models and methods in this paper may be used by utility companies,electricity retailers,market operators,and policy makers to evaluate the consequences of a proactive RDR and the interactions among multi-entities.

Droplet morphology analysis of drop-on-demand inkjet printing

As an accurate 2D/3D fabrication tool,inkjet printing technology has great potential in preparation of micro electronic devices.The morphology of droplets produced by the inkjet printer has a great impact on the accuracy of deposition.In this study,the drop-on-demand(DoD)inkjet simulation model was established,and the accuracy of the simulation model was verified by corresponding experiments.The simulation result shows that the velocity of the droplet front and tail,as well as the time to disconnect from the nozzle is mainly affected by density(ρ),viscosity(μ)and surface tension(σ)of droplets.When the liquid filament is about to disconnect from the nozzle,the filament length and filament front velocity are found to have a linear correlation withσ/ρμand ln(ρ/(μσ1/2)).

Design and Test of Closed Hydraulic Transmission System of 4WD High-clearance Wheeled Sprayer

In conjunction with the working characteristics of the high-clearance wheeled sprayer and the benefits of the closed hydraulic system,a series of reasonable working parameters should be established,and a hydraulic system that fulfills the requisite specifications should be designed.The AMESim software model is employed to construct a closed hydraulic transmission system,and the simulation analysis is then performed according to the data of hydraulic components.According to analysis results,the prototype can be optimized and upgraded,and a verification test is further carried out.The test results demonstrate that the designed closed hydraulic transmission system meets the actual working requirements of the high-clearance wheeled sprayer and provides a stable experimental platform for intelligent control of agricultural machinery.

Enhancing the reusability and interoperability of artificial neural networks with DEVS modeling and simulation

Artificial neural networks(ANNs),a branch of artificial intelligence,has become a very interesting domain since the eighties when back-propagation(BP)learning algorithm for multilayer feed-forward architecture was introduced to solve nonlinear problems.It is used extensively to solve complex nonalgorithmic problems such as prediction,pattern recognition and clustering.However,in the context of a holistic study,there may be a need to integrate ANN with other models developed in various paradigms to solve a problem.In this paper,we suggest discrete event system specification(DEVS)be used as a model of computation(MoC)to make ANN models interoperable with other models(since all discrete event models can be expressed in DEVS,and continuous models can be approximated by DEVS).By combining ANN and DEVS,we can model the complex configuration of ANNs and express its internal workings.Therefore,we are extending the DEVS-based ANN proposed by Toma et al.[A new DEVS-based generic art-ficial neural network modeling approach,The 23rd European Modeling and Simulation Symp.(Simulation in Industry),Rome,Italy,2011]for comparing multiple configuration parameters and learning algorithms and also to do prediction.The DEVS models are described using the high level language for system specification(HiLLS),[Ma¨ıga et al.,A new approach to modeling dynamic structure systems,The 29th European Modeling and Simulation Symp.(Simulation in Industry),Leicester,United Kingdom,2015]a graphical modeling language for clarity.The developed platform is a tool to transform ANN models into DEVS computational models,making them more reusable and more interoperable in the context of larger multi-perspective modeling and simulation(MAS).

Modeling and simulation of twin-tube hydraulic shock absorber thermodynamic characteristics and sensitivity analysis of its influencing factors

In order to find out the sensitivity of the thermophysical and structural parameters to the thermodynamic characteristics of twin-tube hydraulic shock absorbers,based on the bench test,a method for calculating the time-varying rate of the external work on the shock absorber oil is proposed.And then,a thermodynamic model of the twin-tube hydraulic shock absorber is established by using the basic thermodynamic principles.By analyzing the influence of each parameter on the thermodynamic characteristics of the shock absorber,it can be seen that,the radius of the working cylinder outer wall has the greatest influence on the temperature rise of the shock absorber,followed by the thermal conductivity of the oil,the height of the oil,the heat transfer length of the cylinder barrel,the radius of the oil storage cylinder outer wall,the emissivity of the oil storage cylinder outer wall,the height of the nitrogen,the thermal conductivity of the nitrogen,the specific heat capacity of the oil,the density of the oil,the thermal conductivity of the cylinder,and the mass of the working oil.The kinematic viscosity of the oil has the least influence on the temperature rise of the shock absorber.The research can provide an effective theoretical guidance and reference for the design of the twin-tube hydraulic shock absorber.

A modeling and simulation framework for UAVs utilizing 4G-LTE cellular networks

Only a small amount of work has been published on the topic of exploiting existing Long-Term Evolution-Advanced(LTE)cellular communication network infrastructure for Unmanned Aerial Vehicles(UAV)data links.This paper documents a modeling and simulation(m&s)framework that has been developed utilizing the powerful OMNeT++simulation tool for assessing the feasibility and effectiveness of this prospect in various UAV scenarios.Using multiple scenarios,we have studied the data rate requirements for communications between small and medium-sized UAVs and base stations.Using this framework,we have shown that the data rate requirements for the links are within the data throughput achieved by LTE networks.The developed framework implements a propagation model endorsed by the 3GPP LTE project team and also accurately models the high mobility of UAVs.The framework is highly configurable and extensible and boasts of automatic aggregation of results and chart plotting.The outcomes of this research may be utilized by industry for rapidly deploying highly mobile,low-cost UAVs in a wide range of applications and scenarios.

Modeling and simulation methods of sea clutter based on measured data

The modeling and simulation of sea clutter are important in detecting radar targets in sea backgrounds.Because the nonstationary property of sea clutter is ignored in traditional statistical models,a new method based on measured sea clutter is proposed in this paper.First,we convert the measured sea clutter data under different sea conditions[xI,xQ]into real amplitude SM.Instantaneous phaseθis then extracted from the coherent radar’s baseband data.Second,we select a candidate statistic model and estimate its parameters based on SM by utilizing maximum likelihood estimation.Finally,we generate random series A using corresponding random data generator and then add instantaneous phaseθinto A,i.e.,y=Ae^(jθ),to obtain simulated sea clutter series.Through a comparison of simulated sea clutter and measured sea clutter data via histogram,the validity of the proposed method is proved.

Modeling and simulation of railway vehicle vertical dynamic behavior by considering the effect of passenger-carbody coupling vibration

In order to reflect the vertical random vibration characteristics of railway vehicles more truly and effectively,this paper regards the human body as a single-degree-of-freedom system attached to the bottom of the carriage,and establishes a vertical dynamic model of railway vehicles by considering the influence of the coupling vibration effect between the passenger and the car body.The correctness of the model is verified by the real vehicle test.Then,the influence of the passengers on the vertical vibration characteristics of railway vehicles is analyzed,and the influence of the railway vehicle vibration on the vertical vibration characteristics of passengers is discussed in this paper.The research made in this paper can provide an effective model reference for the analysis of the vertical random vibration characteristics of railway vehicles and passengers,and for the optimization design of the suspension system parameters.

Modeling and simulation as a service architecture for deploying resources in the Cloud

In recent years,Cloud Computing has become popular to facilitate the use of Modeling and Simulation(M&S)resources.Nevertheless,there are still various issues to solve,including the structure constrain of chosen web service frameworks,the sharing of varied resources in the Cloud,and the difficulties in reproducing experiments.We show a new architecture based on Cloud Computing and new modeling methods to deal with these issues.This layered architecture,called Cloud Architecture for Modeling and Simulation as a Service(CAMSaaS),simplifies the deployment of M&S resources as services in the Cloud.CAMSaaS supports hierarchical resource services,experimental frameworks,scalable infrastructure and makes everything as a service.We deploy varied M&S resources as services in the Cloud,and build a Modeling and Simulation as a Service(MSaaS)middleware called CloudRISE to manage a variety of M&S resources.We also use the experimental framework concept to simplify the management of experiment environments.We present a case study for crowd evacuation application using the architecture.

A Collaborative Platform for Complex Product Development Based on Multi-Domain Unified Modeling and Simulation

In order to intensify market competition, manufacturing enterprises must improve their product innovation capability. It is difficult to integrate the system modeling, simulation and collaborative process management in complex product development. A collaborative platform for complex product development based on multi-domain unified modeling and simulation is proposed in this paper. The architecture of the platform is firstly stated. The idea and realization of three key technologies, i.e. multi-domain modeling and simulation for complex product, knowledge management for product design and simulation, multi-domain collaborative mechanism, are emphasized. Finally, an industry case is given. The demonstration of the system shows that integration architecture is the effective infrastructure for multi-domain collaborative product development.