Assessing the expectations associated with pharmaceutical pill colour and shape

Two experiments are reported in which people’s sensory, hedonic, and efficacy expectations associated with pharmaceutical pills of differing colour and shape were assessed. In Experiment 1, 101 participants from the USA viewed online photos of tablets having one of 7 colours and 3 shapes. The participants had to arrange the 21 tablets based on the expectations generated solely by the tablets’ visual properties. The results revealed that the colour of the tablets influenced expected bitterness, expected alertness, and expected efficiency in combating headaches, whereas the shape of the tablets influenced the expected difficulty of swallowing. In Experiment 2, the major findings of Experiment 1 were replicated while using a greater variety of colours, in 358 participants from China, Colombia, and the USA. Importantly, the results revealed some shared expectations across cultures, such as the high expected efficacy of white tablets in combating headaches, or the high expected difficulty of swallowing the diamond-shaped tablets. The results also revealed some differences among the three groups, such as that the colour of the pills influenced how difficult the Chinese participants (but not the other two groups) expected the pills would be to swallow. These findings clearly demonstrate that the differing colours and shapes of pharmaceutical pills set-up significantly different expectations which likely play an important role in terms of people’s subsequent experience.     

Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

Simulating the psychological experience of human vision，a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly，based on the spectral and texture information，the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally，three types of identified road information are verified and merged，and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye，and the overall classification accuracy is higher，indicating that the algorithm is effective and feasible and has good use value.     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

NMDA Receptor Modulation of Incidental Learning in Pavlovian Context Conditioning.

Rats exposed to a footshock show conditional fear when reexposed to the shock context. Immediate presentation of shock after placement in the context significantly reduces this fear. Preexposure to the context in the absence of shock, coupled with a minimum preshock interval during training, overcomes this immediate shock deficit. Because rats learn about the context during preexposure and express that learning after being reinforced, the context preexposure effect is an aversive analogue of latent learning. The authors examined the effect of the N-methyl-D-aspartate (NMDA) receptor antagonist D,L-2-amino-5-phosphovalerate (APV) on the facilitatory effect of context preexposure. Rats were preexposed to a chamber after APV administration. The next day they were placed in the same chamber without drug and received shock 35 s later. APV blocked the facilitatory effect of preexposure. Therefore NMDA receptors are important for contextual latent learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On the determination of optimal transition profile of a stepped bar in tension or in torsion by BEM

The objective is to have uniformly distributed tangential stresses on the transition profile of a stepped bar subjected to tensile and torsional loading using an axisymmetric boundary element formulation. The transition curve is represented by the Langragian interpolation polynomial with progressive degrees to avoid shape distortion during the optimization procedure. The calculated result is compared with that obtained by fluid dynamics given in the literature. It is seen that the transition curve obtained in this paper is reasonable.     

与历史的对话与自然的交流—解析衢州市花园岗中心区城市设计

以衢州市花园岗中心区为例,提出城市设计要在尊重历史文化的基础上,结合自然地理条件,通过创造性的设计手段,来描绘未来城市中心区富有文化和生态内涵的全新形象。     

Windows平台下的汉字输入法机制及应用

作者在Windows平台下，通过对E码汉字输入法系统实现的软件研发过程，本质地认识了Windows平台下的汉字输入法系统的实现原理及其基本方法；本文对Windows IME系统的两个主要组成部分：转换引擎和界面模块以及二者之间的交互关系进行了深入的分析，并揭示了Windows平台下整个汉字输入法系统的底层运转机制。