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)     

Reliability and stability of executive functioning in older adults.

A number of methodological questions have been raised about the reliability and validity of measuring executive functioning (EF) across multiple time points. In this study, correlational and latent-variable analyses were used to examine test-retest reliability of 5 common measures of EF and the stability of a latent EF construct. One hundred eighteen nondemented older adults were tested twice over a 4- to 8-week period. Findings demonstrated modest reliability of individual EF measures but very high stability of a latent EF construct. Relative contributions of each measure to the latent EF factor did not change across measurement trials. In addition, age-related effects on EF were similar at the 2 time points and were within the expected range. Implications for future studies of EF are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Empirically derived subtypes of adolescent depression: Latent profile analysis of co-occurring symptoms in the Treatment for Adolescents with Depression Study (TADS).

A latent profile analysis was conducted on the co-occurring symptoms of 423 adolescents diagnosed with major depressive disorder as part of the Treatment for Adolescents with Depression Study (TADS), a multisite, randomized treatment trial. The participants had a mean (SD) age of 14.6 (1.5) years; of the sample, 45.6% was male and 73.8% was white. Scores on the primary subscales of Conners' Parent Rating Scale-Revised were used as indicators in the analysis. Five classes of symptoms best described the clinical presentation of adolescents enrolled in the TADS. Of the adolescents in the sample, 80% were assigned to classes with clinically significant elevations on 1 or more subscales of the Children's Depression Rating Scale-Revised. The 5 classes met empirical criteria for distinctiveness and were validated against clinical diagnoses, child-rated symptoms, and clinician-rated functional impairment. The findings are consistent with prior studies that showed a high rate of co-occurring symptoms among depressed adolescents. The discussion focuses on understanding subtypes and comorbidity in adolescent depression as well as the implications for treatment and for prevention. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

面向工业平稳/非平稳复杂系统的在线故障监测技术

针对复杂系统中关键性能指标（KPI）相关故障检测方法检测精度低的问题,提出基于双层改进潜结构投影（DL-IPLS）的KPI相关故障检测方法. 利用协整分析和主元分析建立底层模型,对非平稳和平稳变量进行特征提取. 将提取的信息进行融合,建立改进潜结构投影的上层模型,根据融合信息对KPI的贡献进行空间分解. 在2个正交子空间中设计统计量,实现KPI相关故障的在线监测. 田纳西-伊斯曼过程和青霉素发酵过程的仿真结果表明,在面向工业平稳和非平稳复杂工业系统检测时,所提方法有效提高了KPI相关故障的检测率,降低了KPI无关故障的误报率.     

降低炉上温度减少潜热损失

从理论和实验数据论述了降低炉上温度可降低挥发分的逸出量，减少气体带出的粉煤量，进而降低造气过程中的潜热损失。指出控制较低的炉上温度对于降低合成氨造气煤耗具有重大的实际意义。     

校园隐性文化建设问题探究

校园隐性文化建设是校园文化建设的要害和难点,它通过校园环境渗透到师生的思想之中,影响着他们的行为。在进行校园隐性文化研究中,首先要探讨校园隐性文化建设的基本条件,才能寻求到研究对策,顺利开展校园隐性文化建设,进而营造一个良好的校园文化。     

微信息大数据粗糙集的近似约简

为了应对微信息舆情数据的格式复杂、价值稀疏和收集困难等大数据处理技术难题,基于隐含语义分析和粗糙集近似约简理论,设计微信息的数据区间值集和近似匹配分类算法.在不影响数据主要关联关系的原则下,提炼核心属性、消减次要属性,实现一种微信息异常主题倾向的发现方法.结果表明,该近似约简算法能在完成微信息兴趣倾向主题分类的前提下,将数据集属性大幅度缩减,提高微信息的信息挖掘效率,为微信息大数据舆情处理工作提供了新的思路和案例.     

基于LDA和word2vec的英文作文跑题检测

针对目前国内的英语作文辅助批阅系统缺少准确而高效的跑题检测算法的问题,提出了一种结合LDA和Word2vec的跑题检测算法。该算法利用LDA模型对文档建模并通过Word2vec对文档训练,利用得到的文档主题和词语之间的语义关系,对文档中各主题及其特征词计算概率加权和,最终通过设定合理阈值筛选出跑题作文。实验中通过改变文档的主题数而得到的不同F值,确定了最佳主题数。实验结果表明所提出的方法比基于向量空间模型的方法更具有效性,可以检测到更多的跑题作文并且准确率较高,F值达到89%以上,实现了作文跑题检测的智能化处理,可以有效地应用在英语作文教学中。