离心泵并联运行工况点的数值求解

建立了求解多台不同型号离心泵并联运行工况点的数学模型,给出了用数值计算中的“二分法”求解该模型的方法,并附有用Exce l计算的实例。     

Performance discrepancies on the California Verbal Learning Test-Second Edition (CVLT-II) in the standardization sample.

The standardization data for the California Verbal Learning Test-Second Edition (CVLT-II; D. C. Delis, J. H. Kramer, E. Kaplan, & B. A. Ober, 2000) were used to evaluate the base rate of 6 specific discrepancies between various key variables. The results indicated that CVLT-II performance discrepancies should equal or exceed 1 or 1.5 z score points (depending on the individual comparison) in the hypothesized direction to be considered potentially unusual. However, because about 1 in 3 persons in the standardization sample displayed at least 1 such large discrepancy, it is concluded that these base rates should be viewed only as a starting point for interpretation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于PC机群的大地电磁Occam反演并行计算研究

Occam反演以其稳定收敛和不依赖于初始模型的特性被广泛应用于大地电磁数据的处理，但偏导数矩阵的计算和拉格朗日乘子的求取导致大量的模型正演，使得反演速度较低。为此，研究了用基于PC机群的并行计算来解决这一问题的方法。首先对Occam反演方法进行了阐述；然后，分析了反演方法中各计算耗费的时间，提出对约占计算量90％的偏导数和拉格朗日乘子进行并行计算的思想，即偏导数计算采用频点计算一级的大粒度并行，拉格朗日乘子扫描和一维搜索分别采用弘值计算一级的大粒度并行和频点计算一级的小粒度并行；给出了并行计算的实现方法，即在PC机群上，利用主一从编程模式实现Occam反演的整体并行计算。在计算中，采用任务组合方式，减少了通信量，较好地实现了负载均衡。在4节点PC机群上，对应于拉格朗日乘子的扫描和一维搜索方式，整体加速比分别达到3．36和2．83。     

开关电源的平均电流自动均流技术

针对多个开关电源并联时易出现负载电流在各模块间分配不均的现象,介绍了常用的负载电流自动均流法——平均电流自动均流法及其工作特性。并针对其存在母线电压降低的缺陷,提出了一种改进的平均电流自动均流方法,经试验证明均流精度比较高。     

并行算法在软件无线电多DSP平台的应用

近年来，随着软件无线电的发展，用于软件无线电平台中的多DSP并行结构受到越来越多的关注，因为这种结构能提高数字信号处理的速度。提出了一种适合在该平台上并行运算的算法，以多阶FIR滤波器为例，验证了算法，并探讨算法的性能，给出了该算法在多处理器条件下，与单处理器处理结果的比较。对选取合适的软件无线电中频处理多处理器平台具有一定的参考价值，并对舰载软件无线电的实现提供了科学参考。     

Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

串行及并行A/D转换器在高速数据采集中的采样差别性分析

串行和并行接口模式是A/D转换器诸多分类中的一种,但却是应用中器件选择的一个重要指标.在同样的转换分辨率及转换速度的前提下,不同的接口方式不但影响了电路结构,更重要的是将在高速数据采集的过程中对采样周期产生较大影响.本文通过12位串行ADC ADS7822和并行ADC ADS774与AT89C51的接口电路,给出二者采样时间的差异性.     

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。