Improving negotiations with bar charts: The advantages of priority awareness

Negotiations seldom lead to optimal results for the negotiators. The missing knowledge about the priorities of the negotiating parties is one known reason for this. This experimental study examines the effects of priority awareness on different measures of negotiation outcomes. Priority awareness is the awareness of one negotiator about the priorities of the other negotiator. One hundred thirty-two participants were randomly assigned to negotiation pairs in an experimental condition with priority awareness – created implicitly through the usage of an ordinary bar chart – or a control condition without priority awareness. They took over the roles of a car seller or buyer and negotiated within an experimental negotiation support system. They were neither explicitly instructed to use the bar chart in the negotiation or about its benefits, nor were they restricted in sharing any kind of information. The experimental condition showed not only a significantly higher negotiation performance in the form of joint outcome and pareto efficiency than the control condition, but also a higher impasse rate. Creating awareness about each other's priorities in a negotiation has a positive effect on the negotiation performance without noticeable negative effects on satisfaction with, or fairness and duration of, the negotiation.     

Maxsim2—Real-time interactive simulations for computer-assisted teaching of pharmacokinetics and pharmacodynamics

We developed a computer program for use in undergraduate and graduate courses in pharmacology, pharmacokinetics and pharmacodynamics. This program can also be used in environmental and toxicological studies and preclinical simulation, to facilitate communication between modeling pharmacokineticists and project leaders or other decision-makers in the pharmaceutical industry. The program simulates the drug delivery and transport by means of (I) a six-compartment physiological pharmacokinetic flow model, (II) a system of traditional compartment models, or (III) a target-mediated drug disposition system. The program also can be used to simulate instantaneous equilibria between concentration and pharmacodynamic response, or as temporal delays between concentration and response. The latter is done by means of turnover models (indirect response models). Drug absorption, distribution, and elimination are represented by differential equations, which are described by organ and tissue volumes or other volumes of distribution, blood flows, clearance terms, and tissue-to-blood partition coefficients. The user can control and adjust these parameters by means of a slider in real time. By interactively changing the parameter values and simultaneously displaying the resulting concentration–time and/or response–time profiles, users can understand the major mechanisms that govern the disposition or the pharmacological response of the drug in the organism in real time. Schedule dependence is typically seen in clinical practice with a non-linear concentration–response relationship, and is difficult to communicate except via simulations. Here, we sought to illustrate the potential advantages of this approach in teaching pharmacology, pharmacokinetics, and pharmacodynamics to undergraduate pharmacy-, veterinary-, and medical students or to project teams in drug discovery/development.     

Execution profiling blueprints

Although traditional approaches to code profiling help locate performance bottlenecks, they offer only limited support for removing these bottlenecks. The main reason is the lack of detailed visual runtime information to identify and eliminate computation redundancy. We provide three profiling blueprints that help identify and remove performance bottlenecks. The structural distribution blueprint graphically represents the CPU consumption share for each method and class of an application. The behavioral distribution blueprint depicts the distribution of CPU consumption along method invocations and hints at method candidates for caching optimizations. The behavioral evolution blueprint compares profiles of different versions of a software system and highlights performance‐critical changes in the system. These three blueprints helped us to significantly optimize Mondrian, an open source visualization engine. Our implementation is freely available for the Pharo development environment and has been evaluated in a number of different scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

A web-based,interactive visualization tool for social environmental survey data

Understanding human motivations and actions related to environmental problems is central to modeling complex, human-natural systems. However, social science survey data on environmental issues are often presented in relatively static reports and figures and are not easily accessible for participatory deliberation. Federal data sharing mandates motivate innovative data visualization and sharing mechanisms. We developed an open-source, web-based Survey Data Viewer as a visual interface to explore quantitative social science survey data. We used the Python Django web framework and the D3.js visualization library to create and deploy the tool. The Viewer was implemented using a water-related survey administered to a large, random sample of Utah adults in public venues. The Viewer allows users to visualize question responses based on demographic variables with percentages and mean response levels. We developed a standardized template for encoding survey data and metadata that permits the generalization of the tool to other similar surveys.     

A GIS-based software for forecasting pollutant drift on coastal water surfaces using fractional Brownian motion: A case study on red tide drift

For ocean pollution emergencies, decision-makers need to quickly know the location of the pollutant for quick assessment and response strategies. In this study, an integrated operational forecasting model coupling a non-Fickian particle-tracking diffusion model based on fractional Brownian motion and geographic information system (GIS) has been developed to implement an operating system for pollutant drift forecasting. The software was developed in C# and C++ language using ArcGIS Engine functions which provides improved visualization and user-friendly and automatic tools for simulation in a geographically referenced environment. The capabilities and effectiveness of the developed software were illustrated by predicting red tide drift through calibration with field observations. This visualized operational forecasting software provides a quick and easy deployable tool for decision-makers in quick response to emergency ocean pollution events.     

An application software for visualization and control configuration selection of interconnected processes

This paper presents a new application software for control configuration selection of interconnected industrial processes, called ProMoVis. Moreover, ProMoVis is able to visualize process models and process layout at the physical level together with the control system dynamics. The software consists of a builder part where the visual representation of the interconnected process is created and an analyzer part where the process is analyzed using different control configuration selection tools.The conceptual idea of the software is presented and the subsequent design and implementation of ProMoVis are discussed. The implemented analysis methods are briefly described including their usage and implementation aspects. The use of ProMoVis is demonstrated by an application study on the stock preparation process at SCA Obbola AB, Sweden. The results of this study are compared with the currently used control strategy.The study indicates that ProMoVis introduces a systematic and comprehensive way to perform control configuration selection. ProMoVis has been released under the Apache Open Source license.     

Discretization-based direct random sample generation

An efficient Monte Carlo method for random sample generation from high dimensional distributions of complex structures is developed. The method is based on random discretization of the sample space and direct inversion of the discretized cumulative distribution function. It requires only the knowledge of the target density function up to a multiplicative constant and applies to standard distributions as well as high-dimensional distributions arising from real data applications. Numerical examples and real data applications are used for illustration. The algorithms are implemented in statistical software R and a package dsample has been developed and is available online.     

A novel developed method based on single primer isothermal amplification for rapid detection of Alicyclobacillus acidoterrestris in apple juice

Alicyclobacillus acidoterrestris (A. acidoterrestris), as one of the most major spoilage-causing species within the Alicyclobacillus genus, can survive and multiply in the pasteurization process. Nowadays, A. acidoterrestris has become worldwide issue in the fruit juice industry due to its spore-forming and thermo-acidophilic features. A novel single primer isothermal amplification assay (SPIA) was developed for the rapid detection of A. acidoterrestris in apple juice. This assay was designed to target the 16S rRNA gene with a DNA/RNA chimeric primer. Detection of gene amplification was accomplished by amplification curve, turbidity and addition of single strand DNA binding dye SYBR Green II allowing visualization under ultra violet light. The specificity of the assay was confirmed using 7 strains of A. acidoterrestris and 30 strains of non-A. acidoterrestris. The SPIA was highly sensitive and the detection limit was as low as 4.8 CFU/mL. Furthermore, the apple juice inoculated with 61 CFU/mL of A. acidoterrestris could be detected as positive. The novel SPIA with visualization results was successfully applied for the detection of A. acidoterrestris and exhibited high specificity and sensitivity, making it a powerful tool for the detection of A. acidoterrestris in fruit juice industry and being conveniently applied in developing countries with limited resource.     

地矿三维建模及可视化的研究

地矿三维建模及其三维可视化对地质、矿藏信息的获取及地质现象解释具有十分重要的意义。采用基于TIN的多层DEM方法，实现层状地矿实体模型的三维重构，借助于OpenGL图形库实现了层状实体模型的三维可视化，并对模型进行了光照渲染、漫游和切割等操作。     

地层三维建模及OpenGL下三维可视化研究

地层三维重构及其三维可视化对地质信息的获取和地质解释具有十分重要的意义。对地层模型的三维重构进行了研究,提出了一种基于TIN的地层建模方法,有效地实现了地层模型的三维重构。该建模方法实现简单,构模速度快,适用范围广,并在OpenGL三维图形库下,实现了地层模型的三维可视化。