Implicit Motor Learning in Parkinson's Disease.

Objective: This study examined whether disruption of performance is moderated in Parkinson's disease (PD) patients who acquire their motor behaviors in an implicit manner. Method: Twenty-seven patients with PD learned a hammering task in errorless (implicit) or errorful (explicit) conditions and were tested for robustness of motor performance under a secondary task load, which required them to continuously count backward as they performed the hammering task. Results: Patients in the errorless (implicit) motor learning condition exhibited robustness to secondary task loading, whereas patients in the errorful (explicit) motor learning condition did not. Conclusions: Implicit motor learning techniques should be considered by PD rehabilitation specialists in cases in which existing disruption to movements is exacerbated by conscious control. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

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)     

基于支持向量机的多类分类研究

现今流行的分类方法的重要基础是传统的统计学，前提是要有足够的样本，当样本数目有限时容易出现过学习的问题，导致分类效果不理想。引入支持向量机方法，它基于统计学习理论，采用了结构风险最小化原则代替经验风险最小化原则，较好的解决了小样本学习的问题；又由于采用了核函数思想，把非线性空间的问题转换到线性空间，降低了算法的复杂度。对其相关内容包括优化算法及多类分类问题的解决进行了研究，最后用一个实例说明了该方法的可行性和有效性。     

深井长裸眼跨隔测试新工艺的应用

为减少勘探费用，缩短施工周期，取全取准各项地质资料，采取中途测试工艺。随着深井中途测试不断增多，特别是跨隔支撑测试具有一定施工风险和难度，要求测试质量不断提高。结合油田生产实际，合理选配了地层测试工具仪表，不断改进测试管串和优化施工设计，经盐22井中途跨隔测试应用，获得成功。     

一种高性能的新结构IGBT

提出了一种低功率损耗的新结构IGBT.该新结构的创新点在于其复合耐压层结构,该耐压层包括深扩散形成的n型缓冲层和硼注入形成的透明背发射区两部分.虽然在正常工作条件下,该新结构IGBT工作于穿通状态,但器件仍具有非穿通IGBT(NPT-IGBT)的优良特性.该新结构IGBT具有比NPT-IGBT更薄的芯片厚度,从而可以获得更好的通态压降和关断功耗之间的折衷.实验结果表明:与NPT-IGBT相比较,新结构IGBT的功率损耗降低了40%.     

An intelligent web-page classifier with fair feature-subset selection

The explosion of on-line information has given rise to many manually constructed topic hierarchies (such as Yahoo!!). But with the current growth rate in the amount of information, manual classification in topic hierarchies results in an immense information bottleneck. Therefore, developing an automatic classifier is an urgent need. However, classifiers suffer from enormous dimensionality, since the dimensionality is determined by the number of distinct keywords in a document corpus. More seriously, most classifiers are either working slowly or they are constructed subjectively without any learning ability. In this paper, we address these problems with a fair feature-subset selection (FFSS) algorithm and an adaptive fuzzy learning network (AFLN) for classification. The FFSS algorithm is used to reduce the enormous dimensionality. It not only gives fair treatment to each category but also has ability to identify useful features, including both positive and negative features. On the other hand, the AFLN provides extremely fast learning ability to model the uncertain behavior for classification so as to correct the fuzzy matrix automatically. Experimental results show that both FFSS algorithm and the AFLN lead to a significant improvement in document classification, compared to alternative approaches.     

Preschool Competency in Context: An Investigation of the Unique Contribution of Child Competencies to Early Academic Success.

The present concurrent study combined developmental and ecological considerations to examine the unique contribution of multiple preschool competencies to an indicator of early academic success. Participants included 195 Head Start children from 32 classrooms representative of a large, urban Head Start program. Dimensional (variable-centered) analyses revealed 3 distinct classroom competency dimensions (i.e., General Classroom Competencies, Specific Approaches to Learning, and Interpersonal Classroom Behavioral Problems). The first 2 of these dimensions were found to be uniquely associated with early academic success. Findings from typological (person-centered) analyses supported the dimensional findings. Typological analyses revealed 7 profiles of classroom competency distinguished by high scores on the dimensions of General Competencies and Approaches to Learning, and these profiles were found to relate differentially to the indicator of early academic success. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

西部地区深井井身结构设计技术探讨

科学合理地确定井身结构及钻井液密度是深井超深井钻井的关键环节之一，其基础是准确建立地层孔隙压力、地应力、破裂压力、坍塌压力的钻前预测剖面。分析了西部地区目前深井井身结构的缺点和进行井身结构应考虑的问题，介绍了深探井井身结构的设计方法，并针对西部复杂地区的地层特点，建议采用3种增加技术套管的井身结构方案。塔河油田钻井实践表明，采用这3种井身结构方案后，深井机械钻速得到提高，钻井周期缩短，而且降低了钻井成本。     

一种T-S型动态模糊推理模型的建模算法研究

以一种进化聚类算法（ECM）为基础,提出了一种新的T-S型动态模糊推理模型的建模算法.以往许多神经模糊模型都不适用于自适应在线学习,而文章模型能够实时地调整模糊规则库及规则参数,具有较强的在线学习能力.仿真结果表明,该方法是有效的.     

A Revised Methodology for Research on Metamemory: Pre-judgment Recall And Monitoring (PRAM).

A revised methodology is described for research on metacognitive monitoring, especially judgments of learning (JOLs), to investigate psychological processing that previously has been only hypothetical and unobservable. During data collection a new stage of recall occurs just prior to the JOL, so that during data analysis the items can be partitioned into subcategories to measure the degree of JOL accuracy in ways that are more analytic than was previously possible. A weighted-average combinatorial rule allows the component measures of JOL accuracy to be combined into the usual overall measure of metacognitive accuracy. An example using the revised methodology offers a new explanation for the delayed-JOL effect, in which delayed JOLs are more accurate than immediate JOLs for predicting recall. (PsycINFO Database Record (c) 2010 APA, all rights reserved)