Long-term high fructose and saturated fat diet affects plasma fatty acid profile in rats

As the consumption of fructose and saturated fatty acids (FAs) has greatly increased in western diets and is linked with an increased risk of metabolic syndrome, the aim of this study was to investigate the effects of a moderate (10 weeks) and a prolonged (30 weeks) high fructose and saturated fatty acid (HFS) diet on plasma FA composition in rats. The effects of a few weeks of HFS diet had already been described, but in this paper we tried to establish whether these effects persist or if they are modified after 10 or 30 weeks. We hypothesized that the plasma FA profile would be altered between 10 and 30 weeks of the HFS diet. Rats fed with either the HFS or a standard diet were tested after 10 weeks and again after 30 weeks. After 10 weeks of feeding, HFS-fed rats developed the metabolic syndrome, as manifested by an increase in fasting insulinemia, total cholesterol and triglyceride levels, as well as by impaired glucose tolerance. Furthermore, the plasma FA profile of the HFS group showed higher proportions of monounsaturated FAs like palmitoleic acid [16:1(n-7)] and oleic acid [18:1(n-9)], whereas the proportions of some polyunsaturated n-6 FAs, such as linoleic acid [18:2(n-6)] and arachidonic acid [20:4(n-6)], were lower than those in the control group. After 30 weeks of the HFS diet, we observed changes mainly in the levels of 16:1(n-7) (decreased) and 20:4(n-6) (increased). Together, our results suggest that an HFS diet could lead to an adaptive response of the plasma FA profile over time, in association with the development of the metabolic syndrome.     

Predicting crest settlement in concrete face rockfill dams using adaptive neuro-fuzzy inference system and gene expression programming intelligent methods

This paper deals with the estimation of crest settlement in a concrete face rockfill dam （CFRD）, utilizing intelligent methods. Following completion of dam construction, considerable movements of the crest and the body of the dam can develop during the first impoundment of the reservoir. Although there is vast experience worldwide in CFRD design and construction, few accurate experimental relationships are available to predict the settlement in CFRD. The goal is to advance the development of intelligent methods to estimate the subsidence of dams at the design stage. Due to dam zonifieation and uncertainties in material properties, these methods appear to be the appropriate choice. In this study, the crest settlement behavior of CFRDs is analyzed based on compiled data of 24 CFRDs constructed during recent years around the world, along with the utilization of gene ex- pression programming （GEP） and adaptive neuro-fuzzy inference system （ANFIS） methods. In addition, dam height （H）, shape factor （St）, and time （t, time after first operation） are also assessed, being considered major factors in predicting the settlement behavior. From the relationships proposed, the values ofR2 for both equations of GEP （with and without constant） were 0.9603 and 0.9734, and for the three approaches of ANFIS （grid partitioning （GP）, subtractive clustering method （SCM）, and fuzzy c-means clustering （FCM）） were 0.9693, 0.8657, and 0.8848, respectively. The obtained results indicate that the overall behavior evaluated by this approach is consistent with the measured data of other CFRDs.     

EP-based adaptive tracker with observer and fault estimator for nonlinear time-varying sampled-data systems against actuator failures

An evolutionary programming-based adaptive observer is presented in this paper to improve the performance of state estimation of nonlinear time-varying sampled-data systems. Also, this paper presents a novel state-space adaptive tracker together with the proposed observer and estimation schemes for nonlinear time-varying sampled-data systems having actuator failures. For the class of slowly varying nonlinear time-varying systems, the proposed methodology is able to achieve the desired fault detection and performance recovery for the originally well-designed systems, as long as the controller having the high-gain property. For practical implementation, we utilize the advantages of digital redesign methodology to convert a well-designed high-gain analog controller/observer into its corresponding low-gain digital controller/observer. Illustrative examples are given to demonstrate the effectiveness of the proposed method. The developed digitally redesigned adaptive tracker with the proposed observer and estimator is suitable for implementation by using microprocessors.     

图像分割的自适应K均值聚类算法研究

使用K均值聚类算法完成对图像的分割是一种常见的分割技术,针对传统的K均值聚类算法的不足,提出了使用直方图波形的有效波峰个数自适应确定K值的大小,实验结果表明,该方法简单、灵活、容易实现,并能取得较好的结果。     

适应行为研究的新理论——社会性能力理论

随着智力落后儿童教育研究的发展,适应行为的研究已经成为研究 者们关注的一个重要问题。但是,长期以来有关适应行为的研究一直存在争 论。本文将介绍美国心理学家格林斯潘的一个适应行为研究的新理论—— 社会性能力理论的内容、发展以及其的意义。以期对我国智力落后儿童的适 应行为研究有所借鉴。     

SOFC temperature evaluation based on an adaptive fuzzy controller

The operating temperature of a solid oxide fuel cell （SOFC） stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative （PID） control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.     

Adaptive designs for sequential experiments

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Affective response to gambling promotions during televised sport: A qualitative analysis

Gambling promotions extensively punctuate contemporary televised sport broadcasts and concerns have been raised about their potential impacts on vulnerable groups. Research suggests advertising can shape individuals’ emotions, or affect, towards a product/brand and can subsequently influence purchasing decisions. Consequently, understanding how promotion of gambling influences sport viewers is an important although sparsely addressed area of research. This paper presents exploratory research on affective responses towards gambling promotions displayed during televised sport. Eight online focus groups were conducted with a sample of regular sports viewers in Queensland, Australia. Participants were exposed to a variety of gambling promotions used in National Rugby League match telecasts. Utilising adaptive theory, themes reflecting affective responses to each promotional technique were identified. A range of positive and negative affective responses were identified including arousal, joy, anger and worry. A conceptual model representing emergent affective response categories, message delivery techniques and moderating variables is proposed to inform a broader future research agenda examining how gambling promotions during televised sport influence affective response and concomitant gambling intention.     

基于项目反应理论的临床医学考试系统的实现技术

对利用现代科技手段实现临床医学教学活动中学生临床能力的评价做了一些尝试,介绍项目反应理论原理,探讨自适应测验系统中所需要运用的理论,并给出在临床医学学科实际运用时的数学模型及考试设计流程,对存在的具体问题提出自己的设计思路和解决方案。     

Adaptive document clustering based on query-based similarity

In information retrieval, cluster-based retrieval is a well-known attempt in resolving the problem of term mismatch. Clustering requires similarity information between the documents, which is difficult to calculate at a feasible time. The adaptive document clustering scheme has been investigated by researchers to resolve this problem. However, its theoretical viewpoint has not been fully discovered. In this regard, we provide a conceptual viewpoint of the adaptive document clustering based on query-based similarities, by regarding the user’s query as a concept. As a result, adaptive document clustering scheme can be viewed as an approximation of this similarity. Based on this idea, we derive three new query-based similarity measures in language modeling framework, and evaluate them in the context of cluster-based retrieval, comparing with K-means clustering and full document expansion. Evaluation result shows that retrievals based on query-based similarities significantly improve the baseline, while being comparable to other methods. This implies that the newly developed query-based similarities become feasible criterions for adaptive document clustering.