Impairment in long-term retention but not short-term performance on a water maze reversal task following hippocampal or mediodorsal striatal n-methyl-d-aspartate receptor blockade.

Male Long-Evans rats were injected with 32 ng/μl of the N-methyl-D-aspartate (NMDA) receptor antagonist 3-(2-carboxypiperazin-4-yl) propyl-1-phosphonic acid (CPP) or vehicle and trained to locate a hidden platform in a different location (reversal training) than used on the initial 4 days of training. Rats treated with vehicle or CPP into the dorsal hippocampus, basolateral amygdala, or mediodorsal striatum had similar latencies to locate the platform on the reversal day. Rats infused with CPP into the dorsal hippocampus or mediodorsal striatum failed to search preferentially in the novel location during a 24-hr, drug-free retention test, whereas all other groups searched preferentially in this location. Therefore, blocking dorsal hippocampal or mediodorsal striatal NMDA receptors selectively blocked long-term spatial retention without producing short-term performance deficits. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimistic Personality and Psychosocial Well-Being During Treatment Predict Psychosocial Well-Being Among Long-Term Survivors of Breast Cancer.

In considering well-being among survivors of life-threatening illnesses such as breast cancer, 2 important questions are whether there is continuity between initial adjustment and longer term adjustment and what role personality plays in long-term adjustment. In this research, a sample of 163 early stage breast cancer patients whose psychosocial adjustment was first assessed during the year after surgery completed the same measures 5-13 years after surgery. Initial reports of well-being were relatively strong predictors of follow-up well-being on the same measures. Initial optimism and marital status also predicted follow-up adjustment, even controlling for earlier adjustment, which exerted a substantial unique effect in multivariate analyses. In contrast, initial medical variables played virtually no predictive role. There is substantial continuity of subjective well-being across many years among survivors of breast cancer, rooted partly in personality and social connection. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling Task Switching Without Switching Tasks: A Short-Term Priming Account of Explicitly Cued Performance.

Switch costs in task switching are commonly attributed to an executive control process of task-set reconfiguration, particularly in studies involving the explicit task-cuing procedure. The authors propose an alternative account of explicitly cued performance that is based on 2 mechanisms: priming of cue encoding from residual activation of cues in short-term memory and compound cue retrieval of responses from long-term memory. Their short-term priming account explains the repeated cue encoding benefit, switch cost, reduction in switch cost with preparation time, and other effects. The authors develop a mathematical model of their priming account and fit it to data from 3 experiments, demonstrating that a set of basic psychological processes can produce several effects--including putative switch costs--without switching tasks. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

用于中子剂量当量仪校准的同位素中子参考辐射的建立

建立了三种辐射中子源项的同位素中子参考辐射场,对有关技术内容和方法以及达到的技术指标进行了总结;介绍了参考辐射场的标准化中子参数及其测量方法。结果表明,已建立的同位素中子参考辐射满足有关技术规范要求,可用于中子剂量当量仪的校准和检定。     

快速输入超长数字序列的有效方法

本文给出了在Excel中快速输入超长数字序列的两种有效方法.     

Topic Identification in Dynamical Text by Complexity Pursuit

The problem of analysing dynamically evolving textual data has arisen within the last few years. An example of such data is the discussion appearing in Internet chat lines. In this Letter a recently introduced source separation method, termed as complexity pursuit, is applied to the problem of finding topics in dynamical text and is compared against several blind separation algorithms for the problem considered. Complexity pursuit is a generalisation of projection pursuit to time series and it is able to use both higher-order statistical measures and temporal dependency information in separating the topics. Experimental results on chat line and newsgroup data demonstrate that the minimum complexity time series indeed do correspond to meaningful topics inherent in the dynamical text data, and also suggest the applicability of the method to query-based retrieval from a temporally changing text stream. This revised version was published online in June 2006 with corrections to the Cover Date.     

CM-Builder: A Natural Language-Based CASE Tool for Object-Oriented Analysis

Graphical CASE (Computer Aided Software Engineering) tools provide considerable help in documenting the output of the Analysis and Design stages of software development and can assist in detecting incompleteness and inconsistency in an analysis. However, these tools do not contribute to the initial, difficult stage of the analysis process, that of identifying the object classes, attributes and relationships used to model the problem domain. This paper describes an NL-Based CASE tool called Class Model Builder (CM-Builder) which aims at supporting this aspect of the Analysis stage of software development in an Object-Oriented framework. CM-Builder uses robust Natural Language Processing techniques to analyse software requirements texts written in English and constructs, either automatically or interactively with an analyst, an initial UML Class Model representing the object classes mentioned in the text and the relationships among them. The initial model can be directly input to a graphical CASE tool for further refinement by a human analyst. CM-Builder has been quantitatively evaluated in blind trials against a collection of unseen software requirements texts and we present the results of this evaluation, together with the evaluation method. The results are very encouraging and demonstrate that tools such as CM-Builder have the potential to play an important role in the software development process.     

A Machine Learning Approach for Identification Thesis and Conclusion Statements in Student Essays

This study describes and evaluates twoessay-based discourse analysis systems thatidentify thesis and conclusion statements fromstudent essays written on six different essaytopics. Essays used to train and evaluate thesystems were annotated by two human judges,according to a discourse annotation protocol. Using a machine learning approach, a number ofdiscourse-related features were automaticallyextracted from a set of annotated trainingdata. Using these features, two discourseanalysis models were built using C5.0 withboosting: a topic-dependent and atopic-independent model. Both systemsoutperformed a positional algorithm. While thetopic-dependent system showed somewhat higherperformance, the topic-independent systemshowed similar results, indicating that asystem can generalize to unseen data – thatis, essay responses on topics that the systemhas not seen in training.     

DCS组态文本自动映射电站控制系统仿真模型软件开发

介绍一种最新研制的利用电站实际机组DCS组态文本文件自动生成控制系统仿真模型的仿真软件，该软件具有开放、通用、自动化程度高和简单易行的特点，可大大减轻仿真开发工作者的工作量，缩短仿真机研制周期，为DCS的仿真建模提供了一条新的途径。     

基于文档树的XML文件转换

随着互联网与XML技术的不断发展，实现XML文件与非结构化的文本文件之间的相互转换的要求日趋提高，针对该问题，文章提出了一种基于文档树的XML文件转换方法。该方法通过文档树的形式描述文本文件的结构与内容，在特定的映射规则下对文档树进行遍历以实现RTF文件为代表的文本文件与XML文件的相互转换，最后介绍了文档树的构造及相关算法.