Effects of Approach and Avoid Mindsets on Performance, Self-regulatory Cognition, and Affect in a Multi-task Environment

Despite numerous studies of approach- and avoidant mindsets, relatively little research has addressed the impact of such motivational orientations on performance and emotion in a real-time, multi-task setting. A laboratory simulation is reported that examines the influence of an induced approach-centered, an avoidance-centered, and a “neutral” motivational mindset upon multiple aspects of task performance, self-regulatory cognition, and affect. Undergraduate females randomly assigned to one of three mindset conditions performed a simulated automobile drive across one practice and two experimental trials. Dependent measures included divided attention, behavioral indicators of driving “cautiousness” in relatively safe straight roadway sections as well as during more risk-filled driving, multiple aspects of self-regulatory thinking (including self-monitoring, intended effort, and self-administered consequences), and positive and negative affect. Results revealed that the avoidant mindset produced poorer executive attention (i.e., fewer correctly detected divided attention events), more “cautious” driving behavior and reduced performance variability (i.e., greater control) when driving on presumably safe, straight roadway sections, lower self-reports of intended effort, and greater negative affect relative to the approach mindset. Results are intepreted within a self-regulation-centered motivational framework. Implications of the multi-task simulation for the study of normal and disordered adjustment are considered.     

先天性髋脱位骨刀模型的研究

目的：在建立先天性髋脱位（CDH）的计算机三维交互模型的基础上，建立三维骨刀模型，模拟截骨。方法：利用螺旋体积CT获得患儿髋关节扫描数据，用B＋树组织按marching cubes方法完成骨刀模型的重建。通过对B＋树的不完全遍历和回溯，定位表面模型间的交点并分割髋关节模型。结果：重建的骨刀模型与CDH三维模型之间，可进行实时交互。初步实现了对骨性三维交互模型任意位置的平面切割、球面切割、拾取和拼合。结论：此建模、切割方法可行有效，可用于计算机模拟骨性手术的研究。     

Bayesian estimation of a random effects heteroscedastic probit model

Summary Bayesian analysis is given of a random effects binary probit model that allows for heteroscedasticity. Real and simulated examples illustrate the approach and show that ignoring heteroscedasticity when it exists may lead to biased estimates and poor prediction. The computation is carried out by an efficient Markov chain Monte Carlo sampling scheme that generates the parameters in blocks. We use the Bayes factor, cross‐validation of the predictive density, the deviance information criterion and Receiver Operating Characteristic (ROC) curves for model comparison.     

Simulation model of renal replacement therapy: predicting future demand in England.

BACKGROUND: The demand for renal replacement therapy (RRT) in England has risen steadily, although from a lower base than many other developed countries. Predicting the future demand for RRT and the impact of factors such as the acceptance rate, transplant supply and patient survival, is required in order to inform the planning of such services. METHODS: A discrete event simulation model estimates the future demand for RRT in England in 2010 for a range of scenarios. The model uses current prevalence and current and projected future acceptance rates, survival rates and the transitions between modalities to predict future patient numbers. National population and mortality data, published literature and data from the UK Renal Registry and UK Transplant, are used to estimate unmet need for RRT, the impact of changing demography and incidence of Type 2 diabetes, patient haemodialysis (HD) survival and transplant supply. RESULTS: By 2010 the predicted prevalence will have increased from about 30,000 in 2000 to between 42 and 51,000 (900-1000 p.m.p.), an average annual growth of 4.5-6%. Changing transplant supply has a small effect on overall numbers but changes the proportion of patients with functioning graft by up to 8%. Even with an optimistic increase in transplant supply (11% p.a. for 5 years), numbers on HD will continue to rise substantially, especially in the elderly. The factors most influencing future patient numbers are the acceptance rate and dialysis survival. CONCLUSION: This model predicts a substantial growth in the RRT population to 2010 to a rate approaching 1000 p.m.p., particularly in the elderly and those on HD, with a steady state not being reached for at least 25 years.     

金属换热器传热过程的数学模型及应用

应用蒙特卡洛法仿真辐射式金属换热器内的辐射传热过程，建立了换热器综合传热的数学模型，利用概率论原理，把辐射能迁移过程仿真为一定累积概率分面下的随机过程，该模型能较好地反映换热器内传热过程的真实情况，可以计算出换热器内烟气、筒壁、空气的温度和壁面热流分布，以及研究烟气进口温度、换热器筒径和狭逢宽度对换热效果的影响。     

Introducing expert systems to medical students using esta, Expert System Teaching Aid

Medical students are allocated little curriculum time for exposure to expert systems. ESTA, a computer model of an expert system, was developed to make best use of this time. The nature of the students' interaction with ESTA is described, and their reactions to the expert system concepts and the place of expert systems in medicine are presented. A discussion of these reactions draws some conclusions about teaching expert systems in particular, and computers in general, in the basic medical course.     

Prototype system for an MR simulation of intracavitary brachytherapy for cervical cancer: Preliminary results in six cases

We report a newly developed MR simulation system for intracavitary brachytherapy for cervical cancer and subsequent treatment results. MR simulation was performed on six patients. The spatial relationship of the tumor to the bladder, rectum, bowel, applicators, etc. was depicted well. Doses to the tumor and surrounding normal tissues were read from isodose curves superimposed on the T2-weighted sagittal image. This system promises to be useful in customizing the dose distribution.     

头低位限制活动对家兔主要脏器微血管壁通透性的影响

本文报导了用40只白色短毛家兔所做的动物模拟失重实验,得出各脏器微血管通透性的动态反应曲线。并用微循环研究方法,分析了模拟失重时各脏器微血管功能状态与微血管通透性之间的关系;阐述了各脏器微循环功能变化特点;并对变化机理作了初步探讨。     

An algorithm for the automated quantitation of metabolites in in vitro NMR signals.

The quantitation of metabolite concentrations from in vitro NMR spectra is hampered by the sensitivity of peak positions to experimental conditions. The quantitation methods currently available are generally labor intensive and cannot readily be automated. Here, an algorithm is presented for the automatic time domain analysis of high-resolution NMR spectra. The TARQUIN algorithm uses a set of basis functions obtained by quantum mechanical simulation using predetermined parameters. Each basis function is optimized by subdividing it into a set of signals from magnetically equivalent spins and varying the simulated chemical shifts of each of these groups to match the signal undergoing analysis. A novel approach to the standard multidimensional minimization problem is introduced based on evaluating the fit resulting from different permutations of possible chemical shifts, obtained from one-dimensional searches. Results are presented from the analysis of (1)H proton magic angle spinning spectra of cell lines illustrating the robustness of the method in a typical application. Simulation was used to investigate the biggest peak shifts that can be tolerated.